CN110933609A - Service migration method and device based on dynamic environment perception - Google Patents

Service migration method and device based on dynamic environment perception Download PDF

Info

Publication number
CN110933609A
CN110933609A CN201911173740.4A CN201911173740A CN110933609A CN 110933609 A CN110933609 A CN 110933609A CN 201911173740 A CN201911173740 A CN 201911173740A CN 110933609 A CN110933609 A CN 110933609A
Authority
CN
China
Prior art keywords
mec server
service
value
mobile terminal
mec
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201911173740.4A
Other languages
Chinese (zh)
Inventor
钟松延
刘慧琳
黄豪球
张梦蕾
芮兰兰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Aerospace Science And Technology Network Information Development Co ltd
Beijing University of Posts and Telecommunications
Original Assignee
Aerospace Science And Technology Network Information Development Co ltd
Beijing University of Posts and Telecommunications
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Aerospace Science And Technology Network Information Development Co ltd, Beijing University of Posts and Telecommunications filed Critical Aerospace Science And Technology Network Information Development Co ltd
Priority to CN201911173740.4A priority Critical patent/CN110933609A/en
Publication of CN110933609A publication Critical patent/CN110933609A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/08—Reselecting an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/16—Performing reselection for specific purposes
    • H04W36/18—Performing reselection for specific purposes for allowing seamless reselection, e.g. soft reselection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/32—Reselection being triggered by specific parameters by location or mobility data, e.g. speed data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/20—Selecting an access point

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Security & Cryptography (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The embodiment of the invention provides a service migration method and a device based on dynamic environment perception, wherein the method comprises the following steps: predicting the target position reached by the mobile terminal at the next moment of the current moment by sensing the dynamic condition of the mobile terminal; according to the obtained positions of the MEC servers and the communication coverage range of the MEC servers, determining the MEC servers with the communication coverage ranges covering the target positions as candidate MEC servers, selecting the candidate MEC server with the maximum total benefit value to determine as the target MEC server, and notifying the source MEC server to transfer the services on the source MEC server, so that the mobile terminal can be ensured to be continuously communicated with the MEC servers.

Description

Service migration method and device based on dynamic environment perception
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a service migration method and apparatus based on dynamic environment sensing.
Background
With the popularization of 5G wireless networks, the era of centralized big data processing with a cloud computing model as a core has come, and edge type big data processing facing mass data computing generated by network edge equipment is produced. And the mobile edge computing can solve the problems of high time delay, high energy consumption, large load pressure and the like in the cloud computing, and well meets the requirements of users on terminal application programs.
In the context of edge mobile computing, due to the limited coverage of a single server, and end users, for example: the continuous movement of intelligent vehicles and personal intelligent devices causes the quality of service provided by the server to be greatly reduced, even service interruption occurs, and the continuity of the service provided by the server is difficult to ensure, and researchers define the condition as service migration. Service migration is described below with respect to fig. 1.
As shown in FIG. 1, a vehicle carries a user terminal at location L1Using MECs1Service provided by server (Mobile edge Computing) 1, when the user terminal moves to location L3When the user terminal is at MEC1Out of coverage of the server, MEC1The service provided by the server to the user terminal may be interrupted. In order to ensure the user terminalContinuity of end service, MEC needs to be connected1Migration of a service provided by a server to a user terminal to a location L3Nearby MECs3On the server, the services of the user terminals are slave to the MEC1Server migration to MEC3The process of servers is referred to as service migration between MEC servers.
The service migration process mainly virtualizes data to be transmitted provided by the MEC server for the mobile terminal, and sends the virtualized data to be transmitted to the MEC server which can be provided for the mobile terminal, and the transmission and migration of the data to be transmitted need cost. The dynamic changes of the mobile terminal and the network in the service migration process cause the service migration to have certain delay.
Referring to fig. 1, a management system for mobile edge computing in the prior art includes: the mobile terminal comprises a plurality of MEC servers and a cloud server, wherein the MEC server is connected with the mobile terminal at the current moment and is a source MEC server, and the MEC server receiving the migration service from the source MEC server is called a target MEC server. Source MEC that mobile terminal is currently connected to1The server further learns the position change of the user terminal according to the change of the IP address of the user terminal, namely the user terminal is L-slave1Move to L3And reporting the position change of the user terminal to a cloud server, informing each MEC server of the position information of the user terminal by the cloud server, determining whether the MEC server is a target MEC server according to the region where the user terminal arrives by each MEC server, determining whether the target MEC server sends a request to a source MEC server according to the operation condition of the target MEC server, and requesting the source MEC server to transfer the service to the target MEC server or maintaining the service of the mobile terminal and the source MEC server.
In the prior art, when the operation condition of the target MEC server is not good, the source MEC server continues to provide services for the mobile terminal, and the position of the mobile terminal is dynamically changed, when the mobile terminal is far away from the source MEC server, the source MEC server may not continue to provide services for the mobile terminal, which causes the communication between the mobile terminal and the MEC server to be interrupted.
Disclosure of Invention
The embodiment of the invention aims to provide a service migration method and device based on dynamic environment sensing, which are used for solving the problem of communication interruption between a mobile terminal and an MEC server in the prior art. The specific technical scheme is as follows:
in a first aspect, a service migration method based on dynamic environment awareness provided in an embodiment of the present invention is applied to a cloud server in a management system of mobile edge computing, and the method includes:
determining a source mobile edge computing MEC server for providing service for the mobile terminal at the current moment;
acquiring the moving direction and the moving speed of the mobile terminal at the current moment, and predicting the target position reached by the mobile terminal at the next moment of the current moment;
determining each MEC server with a communication coverage range covering a target position as a candidate MEC server according to the position of each MEC server and the communication coverage range of each MEC server which are acquired in advance;
calculating to obtain a calculation capacity profit value, a communication profit value, a time delay profit value and a movement profit value of the first MEC server aiming at the first MEC server; the method comprises the steps that a computing capacity profit value is a value reflecting an available capacity ratio and an available computing capacity value of a first MEC server, a communication profit value is a value reflecting transmission service of the first MEC server and a mobile terminal and migration service of the first MEC server from a source MEC server, a time delay profit value is a value reflecting time required by transmission service and processing service of the first MEC server and the mobile terminal, and a movement profit value is a cosine value of an included angle between a moving direction of the mobile terminal and a connecting line of the first MEC server; the first MEC server is each candidate MEC server in the candidate MEC servers;
for a first MEC server, multiplying a communication profit value of the first MEC server by a first weight to obtain a first product, multiplying a delay profit value by a second weight to obtain a second product, multiplying a computing power profit value by a third weight to obtain a third product, multiplying a motion profit value by a fourth weight to obtain a fourth product, and adding the first product, the second product, the third product and the fourth product to obtain a total profit value;
selecting a first MEC server with the maximum total benefit value, and determining the first MEC server as a target MEC server;
and sending a notification to the source MEC server so that the source MEC server migrates the service provided for the mobile terminal at the current moment to the target MEC server.
Optionally, for the first MEC server, the calculation capability profit value, the communication profit value, the delay profit value, and the sports profit value of the first MEC server are obtained by calculation, including:
for a first MEC server, determining transmission cost required by the mobile terminal and the first MEC server for transmitting service and migration cost for the source MEC server to migrate the service to the first MEC server according to the distance between the mobile terminal and the first MEC server;
multiplying the transmission overhead required by the first MEC server for transmitting the service by the first parameter to obtain a fifth product, multiplying the migration overhead of the source MEC server for migrating the service to the first MEC server by the second parameter to obtain a sixth product, adding the fifth product and the sixth product to obtain an addition result, and determining the addition result as a communication profit value;
determining the ratio of the size of the service of the mobile terminal to the channel bandwidth of the first MEC server as the sending time delay of the mobile terminal sending the service to the first MEC server aiming at the first MEC server;
determining the ratio of the distance between the mobile terminal and the first MEC server to the transmission rate as the propagation delay from the time when the service is sent to the first MEC server from the mobile terminal to the time when the service reaches the first MEC server, wherein the transmission rate is the transmission rate of the service in a channel of the first MEC server;
for a first MEC server, calculating an average value according to queuing delay when the first MEC server receives the service type to obtain total queuing delay needed when the first MEC server processes the service, wherein the service receiving type of the first MEC server comprises: in bursts and in cycles;
determining the sum of the sending delay, the propagation delay and the total queuing delay as a delay gain value of the first MEC server aiming at the first MEC server;
acquiring an available capacity ratio and an available computing capacity value of the first MEC server, wherein the available capacity ratio is a ratio of the remaining space to the total space of the first MEC server, and the available computing capacity value is the available rate of a Central Processing Unit (CPU) of the first MEC server;
for the first MEC server, multiplying the available capacity ratio and the available calculation capacity value of the first MEC server by the third parameter respectively, and adding the multiplication results to obtain a calculation capacity profit value of the first MEC server;
and determining a cosine value of an included angle between the moving direction of the mobile terminal and the connection line of the first MEC server as a motion profit value.
Optionally, the step of determining, for the first MEC server, a transmission cost required by the mobile terminal to transmit the service to the first MEC server according to the distance between the mobile terminal and the first MEC server, and the migration cost for the source MEC server to migrate the service to the first MEC server includes:
aiming at a first MEC server, calculating transmission cost required by the mobile terminal and the first MEC server for transmitting service by using a first preset expression, and calculating migration cost for migrating the service to the first MEC server by using a second preset expression; the first preset expression is:
Figure BDA0002289428260000041
the second preset expression is:
Figure BDA0002289428260000042
wherein u represents a mobile terminal, j represents a first MEC server, disujRepresenting the distance between the mobile terminal u and the first MEC server j,
Figure BDA0002289428260000043
theta represents a parameter, a positive real value is taken, theta is more than or equal to 0 and less than or equal to 1,
Figure BDA0002289428260000044
o stands for Source MEC Server, disojRepresents the distance, δ, between the source MEC server o and the first MEC server jc,δlMu represents a parameter related to the channel bandwidth size, mu ≧ 1, δl≥0,δcE.g. R, R represents a real number set.
Optionally, before the step of sending a notification to the source MEC server to enable the source MEC server to migrate the service provided for the mobile terminal at the current time to the target MEC server, the method for migrating the service based on dynamic environment awareness provided in the embodiment of the first aspect of the present invention further includes:
and connecting the target MEC servers according to the sequence to form an optimal path in the moving direction of the mobile terminal according to the sequence of the target MEC servers.
Optionally, after the step of selecting the first MEC server with the largest total benefit value and determining the first MEC server as the target MEC server, the method for service migration based on dynamic environment awareness provided by the embodiment of the first aspect of the present invention further includes:
selecting a maximum value and a minimum value from the calculation capacity profit value, the communication profit value, the delay profit value and the movement profit value of the target MEC server respectively for each target MEC server;
calculating to obtain a first updating weight, a second updating weight, a third updating weight and a fourth updating weight by using a preset weight calculation formula based on the maximum value and the minimum value;
replacing the first weight with the first updating weight, replacing the second weight with the second updating weight, replacing the third weight with the third updating weight and replacing the fourth weight with the fourth updating weight;
the preset weight calculation formula is as follows:
Figure BDA0002289428260000051
wherein the content of the first and second substances,
Figure BDA0002289428260000052
rij＝yij+1；xi，max＝max1≤j≤4xij，xi，min＝min1≤j≤4xij；
Figure BDA0002289428260000053
i represents the serial number of any moment before the current moment; j represents the serial number of the weight, i is 1,2, 3; j is 1,2,3,4, and when j is 1 and 4, yij＝yij aWhen j takes 2 and 3, yij＝yij b，k＝(ln 4)-1When f isijWhen equal to 0, fijlnfij＝0，xi1，xi2，xi3，xi4The first weight, the second weight, the third weight and the fourth weight are respectively obtained in advance before the current time.
In a second aspect, an embodiment of the present invention provides a service migration apparatus based on dynamic environment awareness, which is applied to a cloud server in a management system of mobile edge computing, and includes:
the mobile terminal comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining a source Mobile Edge Computing (MEC) server which provides service for the mobile terminal at the current moment;
the prediction module is used for acquiring the moving direction and the moving speed of the mobile terminal at the current moment and predicting the target position reached by the mobile terminal at the next moment of the current moment;
a second determining module, configured to determine, according to the position of each MEC server and the communication coverage of each MEC server acquired in advance, each MEC server whose communication coverage covers the target position as a candidate MEC server;
the computing module is used for computing a computing power profit value, a communication profit value, a time delay profit value and a movement profit value of the first MEC server aiming at the first MEC server; the method comprises the steps that a computing capacity profit value is a value reflecting an available capacity ratio and an available computing capacity value of a first MEC server, a communication profit value is a value reflecting transmission service of the first MEC server and a mobile terminal and migration service of the first MEC server from a source MEC server, a time delay profit value is a value reflecting time required by transmission service and processing service of the first MEC server and the mobile terminal, and a movement profit value is a cosine value of an included angle between a moving direction of the mobile terminal and a connecting line of the first MEC server; the first MEC server is each candidate MEC server in the candidate MEC servers;
an obtaining module, configured to, for a first MEC server, multiply a computing power profit value of the first MEC server by a first weight to obtain a first product, multiply a communication profit value by a second weight to obtain a second product, multiply a delay profit value by a third weight to obtain a third product, multiply a movement profit value by a fourth weight to obtain a fourth product, and add the first product, the second product, the third product, and the fourth product to obtain a total profit value;
the third determining module is used for selecting the first MEC server with the maximum total benefit value and determining the first MEC server as a target MEC server;
and the notification module is used for sending a notification to the source MEC server so that the source MEC server migrates the service provided for the mobile terminal at the current moment to the target MEC server.
In a third aspect, an embodiment of the present invention provides a server, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete mutual communication through the communication bus; the machine-readable storage medium stores machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: the method steps of the service migration method based on dynamic environment sensing provided by the first aspect of the embodiment of the invention are realized.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and the computer program is executed by a processor to perform the method steps of the service migration method based on dynamic environment awareness provided in the first aspect of the embodiment of the present invention.
In a fifth aspect, an embodiment of the present invention further provides a computer program product containing instructions, which when run on a computer, causes the computer to execute any one of the above-mentioned methods for service migration based on dynamic environment awareness.
The embodiment of the invention provides a service migration method and device based on dynamic environment perception.A source Mobile Edge (MEC) server for providing service for a mobile terminal at the current moment is determined; acquiring the moving direction and the moving speed of the mobile terminal at the current moment, and predicting the target position reached by the mobile terminal at the next moment of the current moment; determining candidate MEC servers from each MEC server according to the obtained positions of each MEC server and the communication coverage range of each MEC server, wherein the target position is in the coverage range of the candidate MEC servers; calculating to obtain a calculation capacity profit value, a communication profit value, a time delay profit value and a movement profit value of the first MEC server aiming at the first MEC server; for a first MEC server, multiplying a computing capacity profit value of the first MEC server by a first weight to obtain a first product, multiplying a communication profit value by a second weight to obtain a second product, multiplying a delay profit value by a third weight to obtain a third product, multiplying a motion profit value by a fourth weight to obtain a fourth product, and adding the first product, the second product, the third product and the fourth product to obtain a total profit value; selecting a first MEC server with the maximum total benefit value, and determining the first MEC server as a target MEC server; and sending a notification to the source MEC server so that the source MEC server migrates the service provided for the mobile terminal at the current moment to the target MEC server. Compared with the prior art, the embodiment of the invention predicts the target position reached by the mobile terminal at the next moment of the current moment by sensing the dynamic condition of the mobile terminal; according to the obtained positions of the MEC servers and the communication coverage range of the MEC servers, determining the MEC servers with the communication coverage ranges covering the target positions as candidate MEC servers, selecting the candidate MEC server with the maximum total benefit value to determine as the target MEC server, and notifying the source MEC server to transfer the services on the source MEC server, so that the mobile terminal can be ensured to be continuously communicated with the MEC servers. Of course, not all of the advantages described above need to be achieved at the same time in the practice of any one product or method of the invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a service migration process provided by an embodiment of the present invention;
fig. 2 is a flowchart of a service migration method based on dynamic environment sensing according to an embodiment of the present invention;
fig. 3 is a flowchart of implementing step S204 according to an embodiment of the present invention;
fig. 4 is a diagram illustrating the comparison effect of the interrupt time of the service migration method based on dynamic environment sensing and other methods according to an embodiment of the present invention;
fig. 5 is a diagram illustrating a comparison effect of standard deviations of a service migration method based on dynamic environment sensing and other methods according to an embodiment of the present invention;
FIG. 6 is a flow chart of updating weights provided by an embodiment of the present invention;
fig. 7 is a structural diagram of a service migration apparatus based on dynamic environment sensing according to an embodiment of the present invention;
fig. 8 is a block diagram of a server according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 2, a service migration method based on dynamic environment awareness according to an embodiment of the present invention is applied to a cloud server in a management system of mobile edge computing, and includes:
s201, determining a source MEC server providing service for the mobile terminal at the current moment.
It can be understood that the cloud server can obtain the source MEC server providing service for the mobile terminal at the current time by communicating with each MEC server, where the current time refers to the current system time of the cloud server.
S202, the moving direction and the moving speed of the mobile terminal at the current moment are obtained, and the target position of the mobile terminal at the next moment of the current moment is predicted.
The next moment of the current moment is set by taking the current moment as the starting time, starting from the starting time, and at a moment after a preset interval time, the preset interval time can be set according to the distance of each MEC server and the moving speed of the mobile terminal.
For example, if the current time is 10 o 'clock and the preset interval time is half an hour, the next time to the current time is 10 o' clock and half an hour.
And S203, determining each MEC server with the communication coverage range covering the target position as a candidate MEC server according to the position of each MEC server and the communication coverage range of each MEC server which are acquired in advance.
And S204, aiming at the first MEC server, calculating to obtain a calculation capacity profit value, a communication profit value, a time delay profit value and a movement profit value of the first MEC server.
The method comprises the steps that a computing capacity profit value is a value reflecting an available capacity ratio and an available computing capacity value of a first MEC server, a communication profit value is a value reflecting transmission service of the first MEC server and a mobile terminal and migration service of the first MEC server from a source MEC server, a time delay profit value is a value reflecting time required by transmission service and processing service of the first MEC server and the mobile terminal, and a movement profit value is a cosine value of an included angle between a moving direction of the mobile terminal and a connecting line of the first MEC server; the first MEC server is each of the candidate MEC servers.
S205, for the first MEC server, multiplying the communication profit value of the first MEC server by the first weight to obtain a first product, multiplying the delay profit value by the second weight to obtain a second product, multiplying the calculation capacity profit value by the third weight to obtain a third product, multiplying the movement profit value by the fourth weight to obtain a fourth product, and adding the first product, the second product, the third product, and the fourth product to obtain a total profit value.
The first weight, the second weight, the third weight and the fourth weight at the current time are all preset, and can be set to 0.25 in actual setting.
The total benefit value may be calculated using the following expression: r ═ w1Rc+w2Rd+w3Rl+w4cosθtWherein R represents the total benefit value, w1，w2，w3，w4Respectively, a first weight, a second weight, a third weight, and a fourth weight.
S206, selecting the first MEC server with the maximum total benefit value, and determining the first MEC server as the target MEC server.
S207, sending a notification to the source MEC server, so that the source MEC server migrates the service provided for the mobile terminal at the current time to the target MEC server.
As an optional implementation manner of the embodiment of the present invention, as shown in fig. 3, the step S204 may be implemented by:
s2041, for the first MEC server, determining a transmission overhead required for the mobile terminal to transmit the service to the first MEC server according to a distance between the mobile terminal and the first MEC server, and a migration overhead for the source MEC server to migrate the service to the first MEC server.
The distance between the mobile terminal and the first MEC server, and the distance between the source MEC server and the first MEC server refer to the distance in the geographic space.
Optionally, the calculating of the transmission overhead in step 2041 includes calculating, by using a first preset expression, the transmission overhead required by the mobile terminal and the first MEC server to transmit the service, and calculating the migration overhead may include calculating, by using a second preset expression, the migration overhead of the service migrated to the first MEC server by the source MEC server.
Wherein the first preset expression is as follows:
Figure BDA0002289428260000101
the second preset expression is:
Figure BDA0002289428260000102
wherein u represents a mobile terminal, j represents a first MEC server, disujRepresenting the distance between the mobile terminal u and the first MEC server j,
Figure BDA0002289428260000103
theta represents a parameter of transmission overhead, a positive real value is taken and can be preset, theta is more than or equal to 0 and less than or equal to 1,
Figure BDA0002289428260000104
o stands for Source MEC Server, disojRepresents the distance, δ, between the source MEC server o and the first MEC server jc，δlMu represents a parameter of migration overhead, and can be preset, mu is more than or equal to 1, and deltal≥0，δcE.g. R, R represents a real number set.
S2042, multiplying the transmission overhead required by the first MEC server to transmit the service by the first parameter to obtain a fifth product, multiplying the migration overhead of the source MEC server migrating the service to the first MEC server by the second parameter to obtain a sixth product, adding the fifth product and the sixth product to obtain an addition result, and determining the addition result as the communication profit value.
The first parameter and the second parameter are values set according to industry experience, the values of the first parameter and the second parameter can be the same or different, and in practical application, the values of the first parameter and the second parameter can be 0.5.
Based on the above explanation, the communication profit value can be calculated by the following expression: rc＝β1*costcom(disuj)-β2*costmig(disoj) In the formula, RcRepresenting value of communication gain, β1Is the first parameter, β2Is a second parameter, which can be preset to represent the multiplication.
S2043, for the first MEC server, determining a ratio of the size of the mobile terminal service to the channel bandwidth of the first MEC server as a transmission delay for the mobile terminal to transmit the service to the first MEC server.
The size of a service refers to the bit size of a packet of the service.
S2044, determining a ratio of a distance between the mobile terminal and the first MEC server to the transmission rate as a propagation delay from when the service is sent from the mobile terminal to the first MEC server to when the service reaches the first MEC server.
Wherein the transmission rate is a transmission rate in a channel serving the first MEC server.
S2045, for the first MEC server, performing average calculation according to the queuing delay of the first MEC server when receiving the service type, to obtain a total queuing delay required by the first MEC server when processing the service.
Wherein the type of the first MEC server receiving the service comprises: in bursts and in cycles.
The following expression may be used to calculate the transmission delay of the service sent by the mobile terminal to the first MEC server, where the expression is: t is tsdata/BW, where tsWhich represents a transmission delay of the mobile terminal to transmit a service to the first MEC server. The propagation delay from when the service is sent out from the mobile terminal to the first MEC server to when it reaches the first MEC server may be calculated using the following expression: t is tt(di (uj))/v, wherein t istRepresenting the propagation delay from when the service is sent out to the first MEC server to when it arrives at the first MEC server. The calculation at the first MEC server may be performed using the following expressionThe total queuing delay required for service management is as follows:
Figure BDA0002289428260000121
in the formula, trqRepresenting the total queuing delay needed by the first MEC server when processing the service, data being the size of the mobile terminal service, BW being the channel bandwidth of the first MEC server, dis (uj) being the distance between the source MEC server and the first MEC server, v being the transmission rate of data between the mobile terminal and the first MEC server, trqIs the total queuing delay required by the first MEC server to process the service, L refers to the number of bits of data packets per service, rate is the transmission rate (bit/s) of the link, a refers to the number of packets arriving per second of the service, L × a refers to the number of bits arriving per second of the data of the service, when a is 1, if the service arrives at the first MEC server in a periodic fashion, the period is such that the data of the service arrives at the first MEC server in a periodic fashion
Figure BDA0002289428260000122
Then the queue is empty when the service packet arrives, the queuing delay t for each arriving service packet rq20. If the service arrives at the first MEC server in bursts, but there is still some periodicity, assume every time
Figure BDA0002289428260000123
Second, N packet services arrive at the first MEC server at the same time, so that the first packet service arriving at the first MEC server has no queuing delay, and the second packet service arriving at the first MEC server has no queuing delay
Figure BDA0002289428260000124
Nth service packet queuing delay to first MEC server
Figure BDA0002289428260000125
In this case, the period is
Figure BDA0002289428260000126
Average queuing delay
Figure BDA0002289428260000127
Thus will T1And is T2Taking the average of the two, the total queuing delay required for the first MEC server to process the service is obtained
Figure BDA0002289428260000128
S2046, for the first MEC server, determining the sum of the transmission delay, the propagation delay, and the total queuing delay as a delay gain value of the first MEC server.
The time delay gain value of the first MEC server may be calculated by using the following expression: rd＝ts+tt+trqIn the formula, RdRepresenting a latency gain value of the first MEC server.
S2047, the available capacity ratio and the available computing capacity value of the first MEC server are obtained.
Wherein, the available capacity ratio is a ratio of the remaining space to the total space of the first MEC server, and the available computing capacity value is an available rate of a Central Processing Unit (CPU) of the first MEC server.
For example, the available capacity ratio of the first MEC server may be calculated by using the following expression: ratecap＝capfree/capallIn the formula, ratecapRepresenting the available capacity ratio of the first MEC server, the available computability value of the first MEC server may be calculated using the following expression: ratecom＝1-CPUusingIn the formula, ratecomRepresenting an available computing capability value, cap, of a first MEC serverfreeRepresenting the remaining space of the first MEC server, capallRepresenting the total space, CPU, of the first MEC serverusingRepresenting the occupied rate of the central processing unit CPU of the first MEC server.
S2048, for the first MEC server, multiplying the available capacity ratio and the available calculation capability value of the first MEC server by the third parameter, respectively, and adding the multiplication results to obtain the calculation capability profit value of the first MEC server.
Wherein the third parameter is a numerical value which is preset by man according to experience.
For example, when the third parameter takes a value of 0.5, the computing power benefit value of the first MEC server may be calculated using the following expression: r1＝0.5*ratecap+0.5*ratecomIn the formula, R1A computing power profit value of the first MEC server is represented.
S2049, determining a cosine value of an included angle between the moving direction of the mobile terminal and the connection line of the first MEC server as a movement income value.
Wherein the sport profit value cos θt，θtThe included angle between the moving direction of the mobile terminal and the connection line of the first MEC server is indicated.
For example, referring to fig. 1, in a simulation experiment, a vehicle node is used as a mobile terminal, and a movement track data set obtained by performing GPS tracking on a taxi in an estuary of san francisco by a CRA WDAD community is used to design a movement track of the vehicle node. And services and mobility between different vehicle nodes are not considered relevant; setting a coherence time interval, and considering that the motion trail (speed and direction) of the vehicle node in the time interval is kept unchanged; in addition, all vehicle nodes are arranged in a quantifiable map, so that information such as the position (coordinate representation) of each vehicle node, the distance hop count among the vehicle nodes, the motion parameters of the vehicle nodes and the like can be obtained at any time in an experiment. An edge network simulation platform ORBIT (open Access Research test for Next-Generation Wireless Networks) is used for simulating a network of a management system for mobile edge computing, and MEC servers are generally configured on base stations, so that the coverage radius of each MEC server is set to be 2100m, the overlapping area of adjacent MEC servers is set to be 204m, and other parameters are set in a table 1 by referring to the laying of a mobile operator on the base stations and the setting of the coverage range:
TABLE 1 parameter settings
Figure BDA0002289428260000141
In a simulation experiment, 250 interrupted vehicle nodes are set, 25 MEC server nodes are set and are uniformly distributed in an area of 20km by 20km, the vehicle nodes are limited to move in the area of 200km by 200km, the running speeds of the vehicle nodes are randomly distributed according to the range of [10m/s and 20m/s ], the vehicle nodes stop for a short time when moving once, the stopping time is 2s, the running time of each simulation is 100s, data packets are used as service requests, and the request time interval is 1 s.
The performance of the service migration method based on dynamic environment awareness provided by the embodiment of the present invention is analyzed from three aspects as follows:
service interruption time: i.e. the time when a service migrates from a source MEC server that initially served it to a target MEC server. The shorter the service interruption time is, the smaller the influence of the movement of the vehicle node on the running service is, and the better the effect of the service migration method based on the dynamic environment perception provided by the embodiment of the invention is.
Load condition of MEC server. Namely, after the service migration, the smaller the standard deviation value of the available resources on the 25 MEC servers, the better the effect of the service migration method based on the dynamic environment sensing provided by the embodiment of the invention is, the more fair the utilization of the available resources on the MEC servers is, and the load balance is realized.
Referring to fig. 4, fig. 4 is a graph showing a comparison effect of the number of service transitions on the horizontal axis and the number of service transition rounds on the vertical axis, where the line with a cross in fig. 4 represents a non-transition scenario, the line with a solid triangle at the position of the lower fastening line represents a service transition method based on multi-factors, and the line with a solid circle represents a service transition method based on dynamic environment sensing. In fig. 4, the size of the request packet is 32M, and a service migration method based on dynamic environment sensing (this method for short) provided in the embodiment of the present invention compares a never migration scheme with a multi-factor based service migration Method (MADA), in a simulation experiment, migration of service migration from a source MEC server to a target MEC server is completed in 1 round, the service migration is set to be performed in 1000 rounds, a service interruption time is recorded once every 100 rounds, and a service interruption time is recordedThe calculation formula of (1):
Figure BDA0002289428260000151
as shown in fig. 4, the dotted line represents the average value of the service interruption time measured by each solution, and it can be seen that the service interruption time of the non-migration solution is very high, up to 6.3s, which is almost 4 times of the service migration method based on dynamic environment sensing provided by the embodiment of the present invention, because the communication distance is too long as the vehicle node is far away from the source MEC server that starts to provide service calculation, the service interruption time is longer and longer until the service cannot be performed, so that the service cannot be completed normally. Meanwhile, as can be seen from fig. 4, the average value of the service interruption time of the MADA method is larger than the average value of the service interruption time of the method, and the interruption time gradually increases with the increase of the number of rounds, because the capacity and the computing power of the target MEC server are limited, the target MEC server cannot process too many services with the processing of the computing services, which results in the efficiency of the service migration process becoming lower, and the value of the service interruption time of the method is smaller than that of the MADA method, because the method considers the dynamic change of the edge network, but the MADA does not exist, when the number of migration times becomes larger, the migration effect will not be good.
Referring to fig. 5, in fig. 5, a horizontal axis is a comparison effect diagram of the service migration frequency and the number of service migration rounds, and a vertical axis is a standard deviation of available resources of the MEC server, in fig. 5, a solid circle represents a non-migration scheme, a Y-shape represents a service migration method based on multiple factors, and a solid triangle represents a service migration method (this method for short) based on dynamic environment sensing, where the method performs 100 rounds of service migration, and after each round of service migration is completed, an available resource value RE on each MEC server is obtainedjThen calculating the standard deviation of the available resource value
Figure BDA0002289428260000161
The simulation result is as shown in the figure5, the larger the standard deviation value, indicating a larger difference in available resources across all MEC servers, the more unbalanced the load. The non-migration policy is that since service migration is not performed, resources on some MEC servers are not used all the time, and as service requests increase, resources on the MEC servers that initially provide services are continuously used, and the standard deviation is high. The standard difference value of the MADA method fluctuates around 0.57 and is 3 times of the standard difference value of the method, the MADA method considers energy consumption, time delay and migration cost, does not consider the capacity of a node and the mobility of a mobile terminal, the method enables service migration to be more fit with an actual scene by sensing the dynamic change of the edge network in real time, comprehensively considers the available resource condition of the edge node in the whole edge network, formulates a migration path and a target MEC server, realizes load balance and prolongs the survival time of the network.
The embodiment of the invention predicts the target position reached by the mobile terminal at the next moment of the current moment by sensing the dynamic condition of the mobile terminal; according to the obtained positions of the MEC servers and the communication coverage range of the MEC servers, determining the MEC servers with the communication coverage ranges covering the target positions as candidate MEC servers, selecting the candidate MEC server with the maximum total benefit value to determine as the target MEC server, and notifying the source MEC server to transfer the services on the source MEC server, so that the mobile terminal can be ensured to be continuously communicated with the MEC servers.
As an optional implementation manner of the embodiment of the present invention, before the step of S207, the method for migrating a service based on dynamic environment sensing provided by the embodiment of the present invention further includes:
and connecting the target MEC servers according to the sequence to form an optimal path in the moving direction of the mobile terminal according to the sequence of the target MEC servers.
Illustratively, referring to FIG. 1, assume that the vehicle is at L1At a location, the determined target MEC server is an MEC2At L3Determining that the target MEC server is an MEC4At L5The determined target MEC server isMEC5 for moving MEC according to moving direction of vehicle2、MEC4And MEC5The servers are connected to form an optimal path, the optimal path can be notified to the source MEC server, and when a new service comes, the new service can be migrated according to the optimal path.
As an optional implementation manner of the embodiment of the present invention, as shown in fig. 6, before step S206, the method for migrating a service based on dynamic context awareness according to the embodiment of the present invention further includes:
s601, for each target MEC server, selecting a maximum value and a minimum value from the calculation capability profit value, the communication profit value, the delay profit value, and the exercise profit value of the target MEC server, respectively.
The method comprises the steps of selecting a maximum value and a minimum value in the computing power profit values of a target MEC server, selecting a maximum value and a minimum value in the communication profit values of the target MEC server, selecting a maximum value and a minimum value in the delay profit values of the target MEC server, and selecting a maximum value and a minimum value in the sports profit values of the target MEC server.
S602, based on the maximum value and the minimum value, a first updating weight, a second updating weight, a third updating weight and a fourth updating weight are calculated by using a preset weight calculation formula.
S603, replace the first weight with the first updating weight, replace the second weight with the second updating weight, replace the third weight with the third updating weight, and replace the fourth weight with the fourth updating weight.
The preset weight calculation formula is as follows:
Figure BDA0002289428260000181
wherein the content of the first and second substances,
Figure BDA0002289428260000182
rij＝yij+1；xi，max＝max1≤j≤4xij，xi，min＝min1≤j≤4xij；
Figure BDA0002289428260000183
Figure BDA0002289428260000184
i represents the serial number of any moment before the current moment; j represents the serial number of the weight, i is 1,2, 3; j is 1,2,3,4, and when j is 1 and 4, yij＝yij aWhen j takes 2 and 3, yij＝yij b，k＝(ln 4)-1When f isijWhen equal to 0, fijlnfij＝0，xi1，xi2，xi3，xi4The first weight, the second weight, the third weight and the fourth weight are respectively obtained in advance before the current time.
For example, referring to table 2, the horizontal axes in table 2 are the communication profit value, the delay profit value, the computing power profit value, and the exercise profit value, respectively, and P1, P2, and P3 represent the historical time before the different current time, and the weights of the current time can be computed by the weights of the different historical times in table 1 to update the weights of the historical time.
TABLE 2 weights of historical time instants
Figure BDA0002289428260000185
According to the embodiment of the invention, the accuracy of determining the target MEC server can be improved by updating the first weight, the second weight, the third weight and the fourth weight.
As shown in fig. 7, an embodiment of the present invention provides a service migration apparatus based on dynamic environment awareness, which is applied to a cloud server in a management system of mobile edge computing, and includes:
a first determining module 701, configured to determine a source mobile edge computing MEC server that provides a service for a mobile terminal at a current time.
The predicting module 702 is configured to obtain a moving direction and a moving speed of the mobile terminal at the current time, and predict a target position reached by the mobile terminal at a next time of the current time.
The second determining module 703 is configured to determine, according to the position of each MEC server and the communication coverage of each MEC server acquired in advance, each MEC server whose communication coverage covers the target position as a candidate MEC server.
A calculating module 704, configured to calculate, for the first MEC server, a calculation capability profit value, a communication profit value, a delay profit value, and a sports profit value of the first MEC server.
The method comprises the steps that a computing capacity profit value is a value reflecting an available capacity ratio and an available computing capacity value of a first MEC server, a communication profit value is a value reflecting transmission service of the first MEC server and a mobile terminal and migration service of the first MEC server from a source MEC server, a time delay profit value is a value reflecting time required by transmission service and processing service of the first MEC server and the mobile terminal, and a movement profit value is a cosine value of an included angle between a moving direction of the mobile terminal and a connecting line of the first MEC server; the first MEC server is each of the candidate MEC servers.
An obtaining module 705, configured to, for the first MEC server, multiply the communication profit value of the first MEC server by the first weight to obtain a first product, multiply the delay profit value by the second weight to obtain a second product, multiply the calculation capacity profit value by the third weight to obtain a third product, multiply the movement profit value by the fourth weight to obtain a fourth product, and add the first product, the second product, the third product, and the fourth product to obtain a total profit value.
A third determining module 706, configured to select the first MEC server with the largest total benefit value, and determine that the first MEC server is the target MEC server.
A notification module 707, configured to send a notification to the source MEC server, so that the source MEC server migrates the service provided for the mobile terminal at the current time to the target MEC server.
Optionally, the calculation module is specifically configured to:
and aiming at the first MEC server, determining the transmission cost required by the mobile terminal and the first MEC server for transmitting the service and the migration cost for the source MEC server to migrate the service to the first MEC server according to the distance between the mobile terminal and the first MEC server.
Multiplying the transmission overhead required by the first MEC server for transmitting the service by the first parameter to obtain a fifth product, multiplying the migration overhead of the source MEC server for migrating the service to the first MEC server by the second parameter to obtain a sixth product, adding the fifth product and the sixth product to obtain an addition result, and determining the addition result as a communication profit value.
And determining the ratio of the size of the mobile terminal service to the channel bandwidth of the first MEC server as the sending delay of the mobile terminal to send the service to the first MEC server aiming at the first MEC server.
And determining the ratio of the distance between the mobile terminal and the first MEC server to the transmission rate as the propagation delay from the time when the service is sent to the first MEC server from the mobile terminal to the time when the service reaches the first MEC server, wherein the transmission rate is the transmission rate of the service in a channel of the first MEC server.
For a first MEC server, calculating an average value according to queuing delay when the first MEC server receives the service type to obtain total queuing delay needed when the first MEC server processes the service, wherein the service receiving type of the first MEC server comprises: in bursts and in cycles.
And aiming at the first MEC server, determining the sum of the sending delay, the propagation delay and the total queuing delay as a delay gain value of the first MEC server.
And acquiring an available capacity ratio and an available computing capacity value of the first MEC server, wherein the available capacity ratio is a ratio of the remaining space to the total space of the first MEC server, and the available computing capacity value is the available rate of a Central Processing Unit (CPU) of the first MEC server.
And aiming at the first MEC server, multiplying the available capacity ratio and the available computing capacity value of the first MEC server by the third parameter respectively, and adding the multiplication results to obtain the computing capacity profit value of the first MEC server.
And determining a cosine value of an included angle between the moving direction of the mobile terminal and the connection line of the first MEC server as a motion profit value.
Optionally, the calculation module is specifically configured to:
aiming at a first MEC server, calculating transmission cost required by the mobile terminal and the first MEC server for transmitting service by using a first preset expression, and calculating migration cost for migrating the service to the first MEC server by using a second preset expression; the first preset expression is:
Figure BDA0002289428260000201
the second preset expression is:
Figure BDA0002289428260000211
wherein u represents a mobile terminal, j represents a first MEC server, disujRepresenting the distance between the mobile terminal u and the first MEC server j,
Figure BDA0002289428260000212
theta represents a parameter, a positive real value is taken, theta is more than or equal to 0 and less than or equal to 1,
Figure BDA0002289428260000213
o stands for Source MEC Server, disojRepresents the distance, δ, between the source MEC server o and the first MEC server jc，δlMu represents a parameter related to the channel bandwidth size, mu ≧ 1, δl≥0，δcE.g. R, R represents a real number set.
As an optional implementation manner of the embodiment of the present invention, the service migration apparatus based on dynamic environment sensing provided by the embodiment of the present invention further includes:
and the optimal path module is used for connecting the target MEC servers according to the sequence in the moving direction of the mobile terminal and the sequence of the target MEC servers to form an optimal path.
As an optional implementation manner of the embodiment of the present invention, the service migration apparatus based on dynamic environment sensing provided by the embodiment of the present invention further includes:
and the updating module is used for selecting the maximum value and the minimum value from the calculation capacity profit value, the communication profit value, the time delay profit value and the movement profit value of the target MEC server respectively aiming at each target MEC server.
And calculating to obtain a first updating weight, a second updating weight, a third updating weight and a fourth updating weight by using a preset weight calculation formula based on the maximum value and the minimum value.
The first update weight replaces the first weight, the second update weight replaces the second weight, the third update weight replaces the third weight, and the fourth update weight replaces the fourth weight.
The preset weight calculation formula is as follows:
Figure BDA0002289428260000214
wherein the content of the first and second substances,
Figure BDA0002289428260000215
rij＝yij+1；xi，max＝max1≤j≤ 4xij，xi，min＝min1≤j≤4xij；
Figure BDA0002289428260000221
i represents the serial number of any moment before the current moment; j represents the serial number of the weight, i is 1,2, 3; j is 1,2,3,4, and when j is 1 and 4, yij＝yij aWhen j takes 2 and 3, yij＝yij b，k＝(ln 4)-1When f isijWhen equal to 0, fijln fij＝0，xi1，xi2，xi3，xi4The first weight, the second weight, the third weight and the fourth weight are respectively obtained in advance before the current time.
The embodiment of the present invention further provides a server, as shown in fig. 8, including a processor 801, a communication interface 802, a memory 803, and a communication bus 804, where the processor 801, the communication interface 802, and the memory 803 complete mutual communication through the communication bus 804,
a memory 803 for storing a computer program;
the processor 801 is configured to implement the following steps when executing the program stored in the memory 803:
determining a source mobile edge computing MEC server for providing service for the mobile terminal at the current moment;
acquiring the moving direction and the moving speed of the mobile terminal at the current moment, and predicting the target position reached by the mobile terminal at the next moment of the current moment;
determining each MEC server with a communication coverage range covering a target position as a candidate MEC server according to the position of each MEC server and the communication coverage range of each MEC server which are acquired in advance;
calculating to obtain a calculation capacity profit value, a communication profit value, a time delay profit value and a movement profit value of the first MEC server aiming at the first MEC server; the method comprises the steps that a computing capacity profit value is a value reflecting an available capacity ratio and an available computing capacity value of a first MEC server, a communication profit value is a value reflecting transmission service of the first MEC server and a mobile terminal and migration service of the first MEC server from a source MEC server, a time delay profit value is a value reflecting time required by transmission service and processing service of the first MEC server and the mobile terminal, and a movement profit value is a cosine value of an included angle between a moving direction of the mobile terminal and a connecting line of the first MEC server; the first MEC server is each candidate MEC server in the candidate MEC servers;
for a first MEC server, multiplying a communication profit value of the first MEC server by a first weight to obtain a first product, multiplying a delay profit value by a second weight to obtain a second product, multiplying a computing power profit value by a third weight to obtain a third product, multiplying a motion profit value by a fourth weight to obtain a fourth product, and adding the first product, the second product, the third product and the fourth product to obtain a total profit value;
selecting a first MEC server with the maximum total benefit value, and determining the first MEC server as a target MEC server;
and sending a notification to the source MEC server so that the source MEC server migrates the service provided for the mobile terminal at the current moment to the target MEC server.
Compared with the prior art, the embodiment of the invention predicts the target position reached by the mobile terminal at the next moment of the current moment by sensing the dynamic condition of the mobile terminal; according to the obtained positions of the MEC servers and the communication coverage range of the MEC servers, determining the MEC servers with the communication coverage ranges covering the target positions as candidate MEC servers, selecting the candidate MEC server with the maximum total benefit value to determine as the target MEC server, and notifying the source MEC server to transfer the services on the source MEC server, so that the mobile terminal can be ensured to be continuously communicated with the MEC servers.
The communication bus mentioned in the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component.
In yet another embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored, and the computer program, when executed by a processor, implements the steps of any one of the above-mentioned dynamic environment awareness-based service migration methods.
In yet another embodiment, a computer program product containing instructions is also provided, which when run on a computer causes the computer to perform any one of the above-mentioned embodiments of the dynamic context awareness-based service migration method.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the device/server/computer program/storage medium embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.

Claims (10)

1. A service migration method based on dynamic environment perception is applied to a cloud server in a management system of mobile edge computing, and the method comprises the following steps:
determining a source mobile edge computing MEC server for providing service for the mobile terminal at the current moment;
acquiring the moving direction and the moving speed of the mobile terminal at the current moment, and predicting the target position reached by the mobile terminal at the next moment of the current moment;
determining each MEC server with a communication coverage range covering the target position as a candidate MEC server according to the position of each MEC server and the communication coverage range of each MEC server which are acquired in advance;
calculating to obtain a calculation capacity profit value, a communication profit value, a time delay profit value and a movement profit value of a first MEC server aiming at the first MEC server; wherein the computing power profit value is a value reflecting an available capacity ratio and an available computing power value of the first MEC server, the communication profit value is a value reflecting a transmission service between the first MEC server and the mobile terminal and a migration service between the first MEC server and a source MEC server, the delay profit value is a value reflecting a time required for the transmission service and the processing service between the first MEC server and the mobile terminal, and the movement profit value is a cosine value of an included angle between a moving direction of the mobile terminal and a connecting line of the first MEC server; the first MEC server is each of the candidate MEC servers;
for a first MEC server, multiplying a communication profit value of the first MEC server by a first weight to obtain a first product, multiplying the delay profit value by a second weight to obtain a second product, multiplying the calculation capacity profit value by a third weight to obtain a third product, multiplying the movement profit value by a fourth weight to obtain a fourth product, and adding the first product, the second product, the third product and the fourth product to obtain a total profit value;
selecting a first MEC server with the maximum total benefit value, and determining the first MEC server as a target MEC server;
and sending a notification to a source MEC server so that the source MEC server migrates the service provided for the mobile terminal at the current moment to the target MEC server.
2. The method of claim 1, wherein the calculating, for the first MEC server, a computing power benefit value, a communication benefit value, a latency benefit value, and a sports benefit value of the first MEC server comprises:
for a first MEC server, determining transmission overhead required by a mobile terminal and the first MEC server for transmitting service according to the distance between the mobile terminal and the first MEC server, and migration overhead of a source MEC server for migrating the service to the first MEC server;
multiplying a transmission overhead required by the first MEC server for transmitting the service by a first parameter to obtain a fifth product, multiplying a migration overhead of the source MEC server for migrating the service to the first MEC server by a second parameter to obtain a sixth product, adding the fifth product and the sixth product to obtain an addition result, and determining the addition result as a communication profit value;
determining a ratio of a size of a service of the mobile terminal to a channel bandwidth of a first MEC server as a transmission delay of the mobile terminal to transmit the service to the first MEC server for the first MEC server;
determining a ratio of a distance between a mobile terminal and the first MEC server to a transmission rate as a propagation delay from when the service is sent from the mobile terminal to the first MEC server to when the service reaches the first MEC server, wherein the transmission rate is the transmission rate of the service in a channel of the first MEC server;
for a first MEC server, performing average calculation according to queuing delay when the first MEC server receives the type of the service to obtain total queuing delay required by the first MEC server when the first MEC server processes the service, wherein the receiving of the type of the service by the first MEC server includes: in bursts and in cycles;
for a first MEC server, determining the sum of the sending delay, the propagation delay and the total queuing delay as a delay gain value of the first MEC server;
acquiring an available capacity ratio and an available computing capacity value of a first MEC server, wherein the available capacity ratio is a ratio of the remaining space to the total space of the first MEC server, and the available computing capacity value is the available rate of a Central Processing Unit (CPU) of the first MEC server;
for a first MEC server, multiplying the available capacity ratio and the available computing capacity value of the first MEC server by a third parameter respectively, and adding the multiplication results to obtain a computing capacity profit value of the first MEC server;
and determining a cosine value of an included angle between the moving direction of the mobile terminal and the connection line of the first MEC server as a movement income value.
3. The method of claim 2, wherein the step of determining, for the first MEC server, a transmission overhead required for the mobile terminal to transmit the service to the first MEC server according to a distance between the mobile terminal and the first MEC server, and the migration overhead for the source MEC server to migrate the service to the first MEC server comprises:
aiming at a first MEC server, calculating transmission cost required by the transmission of the mobile terminal and the first MEC server through a first preset expression, and calculating migration cost for migrating a service to the first MEC server through a source MEC server through a second preset expression; the first preset expression is as follows:
Figure FDA0002289428250000031
the second preset expression is as follows:
Figure FDA0002289428250000032
wherein u represents a mobile terminal, j represents a first MEC server, disujRepresenting the distance between the mobile terminal u and the first MEC server j,
Figure FDA0002289428250000033
theta represents a parameter, a positive real value is taken, theta is more than or equal to 0 and less than or equal to 1,
Figure FDA0002289428250000034
o stands for Source MEC Server, disojRepresents the distance, δ, between the source MEC server o and the first MEC server jc,δl，μRepresents a parameter related to the channel bandwidth size, mu ≧ 1, δl≥0,δcE.g. R, R represents a real number set.
4. The method of claim 1, wherein prior to the step of sending a notification to a source MEC server to cause the source MEC server to migrate the service currently provided for the mobile terminal to the target MEC server, the method further comprises:
and connecting the target MEC servers according to the sequence to form an optimal path in the moving direction of the mobile terminal according to the sequence of the target MEC servers.
5. The method according to claim 1, wherein after the step of selecting the first MEC server with the largest total benefit value, determined to be the target MEC server, the method further comprises:
selecting a maximum value and a minimum value from a calculation capacity profit value, a communication profit value, a time delay profit value and a movement profit value of each target MEC server;
based on the maximum value and the minimum value, calculating to obtain a first updating weight, a second updating weight, a third updating weight and a fourth updating weight by using a preset weight calculation formula;
replacing the first update weight with the first weight, the second update weight with the second weight, the third update weight with the third weight, and the fourth update weight with the fourth weight;
the preset weight calculation formula is as follows:
Figure FDA0002289428250000041
wherein the content of the first and second substances,
Figure FDA0002289428250000042
rij＝yij+1；xi,max＝max1≤j≤ 4xij，xi,min＝min1≤j≤4xij；
Figure FDA0002289428250000043
i represents the serial number of any moment before the current moment; j represents the serial number of the weight, i is 1,2, 3; j is 1,2,3,4, and when j is 1 and 4, yij＝yij aWhen j takes 2 and 3, yij＝yij b，k＝(ln4)-1When f isijWhen equal to 0, fijln fij＝0，xi1,xi2,xi3,xi4The first weight, the second weight, the third weight and the fourth weight are respectively obtained in advance before the current time.
6. A service migration apparatus based on dynamic environment awareness, applied to a cloud server in a management system of mobile edge computing, the apparatus comprising:
the mobile terminal comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining a source Mobile Edge Computing (MEC) server which provides service for the mobile terminal at the current moment;
the prediction module is used for acquiring the moving direction and the moving speed of the mobile terminal at the current moment and predicting the target position reached by the mobile terminal at the next moment of the current moment;
a second determining module, configured to determine, according to the position of each MEC server and the communication coverage of each MEC server acquired in advance, each MEC server whose communication coverage covers the target position as a candidate MEC server;
the computing module is used for computing a computing power profit value, a communication profit value, a time delay profit value and a movement profit value of a first MEC server aiming at the first MEC server; wherein the computing power profit value is a value reflecting an available capacity ratio and an available computing power value of the first MEC server, the communication profit value is a value reflecting a transmission service between the first MEC server and the mobile terminal and a migration service between the first MEC server and a source MEC server, the delay profit value is a value reflecting a time required for the transmission service and the processing service between the first MEC server and the mobile terminal, and the movement profit value is a cosine value of an included angle between a moving direction of the mobile terminal and a connecting line of the first MEC server; the first MEC server is each of the candidate MEC servers;
an obtaining module, configured to, for a first MEC server, multiply a computing power profit value of the first MEC server by a first weight to obtain a first product, multiply the communication profit value by a second weight to obtain a second product, multiply the delay profit value by a third weight to obtain a third product, multiply the exercise profit value by a fourth weight to obtain a fourth product, and add the first product, the second product, the third product, and the fourth product to obtain a total profit value;
the third determining module is used for selecting the first MEC server with the maximum total benefit value and determining the first MEC server as a target MEC server;
a notification module, configured to send a notification to a source MEC server, so that the source MEC server migrates the service provided for the mobile terminal at the current time to the target MEC server.
7. The apparatus of claim 6, wherein the computing module is specifically configured to:
for a first MEC server, determining transmission overhead required by a mobile terminal and the first MEC server for transmitting service according to the distance between the mobile terminal and the first MEC server, and migration overhead of a source MEC server for migrating the service to the first MEC server;
multiplying a transmission overhead required by the first MEC server for transmitting the service by a first parameter to obtain a fifth product, multiplying a migration overhead of the source MEC server for migrating the service to the first MEC server by a second parameter to obtain a sixth product, adding the fifth product and the sixth product to obtain an addition result, and determining the addition result as a communication profit value;
determining a ratio of the size of the mobile terminal service to a channel bandwidth of a first MEC server as a sending delay of the mobile terminal to send the service to the first MEC server aiming at the first MEC server;
determining a ratio of a distance between a mobile terminal and the first MEC server to a transmission rate as a propagation delay from when the service is sent from the mobile terminal to the first MEC server to when the service reaches the first MEC server, wherein the transmission rate is the transmission rate of the service in a channel of the first MEC server;
for a first MEC server, performing average calculation according to queuing delay when the first MEC server receives the type of the service to obtain total queuing delay required by the first MEC server when the first MEC server processes the service, wherein the receiving of the type of the service by the first MEC server includes: in bursts and in cycles;
for a first MEC server, determining the sum of the sending delay, the propagation delay and the total queuing delay as a delay gain value of the first MEC server;
acquiring an available capacity ratio and an available computing capacity value of a first MEC server, wherein the available capacity ratio is a ratio of the remaining space to the total space of the first MEC server, and the available computing capacity value is the available rate of a Central Processing Unit (CPU) of the first MEC server;
for a first MEC server, multiplying the available capacity ratio and the available computing capacity value of the first MEC server by a third parameter respectively, and adding the multiplication results to obtain a computing capacity profit value of the first MEC server;
and determining a cosine value of an included angle between the moving direction of the mobile terminal and the connection line of the first MEC server as a movement income value.
8. The apparatus of claim 7, wherein the computing module is specifically configured to:
aiming at a first MEC server, calculating transmission cost required by the transmission of the mobile terminal and the first MEC server through a first preset expression, and calculating migration cost for migrating a service to the first MEC server through a source MEC server through a second preset expression; the first preset expression is as follows:
Figure FDA0002289428250000061
the second preset expression is as follows:
Figure FDA0002289428250000071
wherein u represents a mobile terminal, j represents a first MEC server, disujRepresenting the distance between the mobile terminal u and the first MEC server j,
Figure FDA0002289428250000072
theta represents a parameter, a positive real value is taken, theta is more than or equal to 0 and less than or equal to 1,
Figure FDA0002289428250000073
o stands for Source MEC Server, disojRepresents the distance, δ, between the source MEC server o and the first MEC server jc,δlMu represents a parameter related to the channel bandwidth size, mu ≧ 1, δl≥0,δcE.g. R, R represents a real number set.
9. A server is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing the communication between the processor and the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any one of claims 1 to 5 when executing a program stored in the memory.
10. A storage medium comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: carrying out the method steps of any one of claims 1 to 5.
CN201911173740.4A 2019-11-26 2019-11-26 Service migration method and device based on dynamic environment perception Pending CN110933609A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911173740.4A CN110933609A (en) 2019-11-26 2019-11-26 Service migration method and device based on dynamic environment perception

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911173740.4A CN110933609A (en) 2019-11-26 2019-11-26 Service migration method and device based on dynamic environment perception

Publications (1)

Publication Number Publication Date
CN110933609A true CN110933609A (en) 2020-03-27

Family

ID=69852029

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911173740.4A Pending CN110933609A (en) 2019-11-26 2019-11-26 Service migration method and device based on dynamic environment perception

Country Status (1)

Country Link
CN (1) CN110933609A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111641891A (en) * 2020-04-16 2020-09-08 北京邮电大学 Task peer-to-peer unloading method and device in multi-access edge computing system
CN112788109A (en) * 2020-12-29 2021-05-11 哈尔滨工业大学 Service migration method and system based on mobile prediction and multi-layer service deployment
CN114217881A (en) * 2022-02-23 2022-03-22 北京航空航天大学杭州创新研究院 Task unloading method and related device
CN114756367A (en) * 2022-04-15 2022-07-15 中国电信股份有限公司 Service migration method, device, medium and electronic equipment
CN115033371A (en) * 2022-08-11 2022-09-09 湖南大学无锡智能控制研究院 Method, equipment and system for service migration in vehicle network

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107919986A (en) * 2017-11-09 2018-04-17 北京邮电大学 VM migrates optimization method between MEC nodes in super-intensive network
CN108064062A (en) * 2018-02-13 2018-05-22 中国联合网络通信集团有限公司 A kind of method and device of information processing across base station
CN108282801A (en) * 2018-01-26 2018-07-13 重庆邮电大学 A kind of switch managing method based on mobile edge calculations
CN108616816A (en) * 2018-05-07 2018-10-02 重庆邮电大学 A kind of track of vehicle prediction and MEC application moving methods based on limit study
CN108632813A (en) * 2018-05-21 2018-10-09 北京邮电大学 The motion management method and system of mobile edge calculations
CN109391681A (en) * 2018-09-14 2019-02-26 重庆邮电大学 V2X mobility prediction based on MEC unloads scheme with content caching
CN110177379A (en) * 2019-06-03 2019-08-27 中国科学院计算机网络信息中心 Base station access method and system
US10660003B2 (en) * 2017-11-03 2020-05-19 Hon Hai Precision Industry Co., Ltd. Methods and related devices for optimizing a mobile edge computing (MEC) system

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10660003B2 (en) * 2017-11-03 2020-05-19 Hon Hai Precision Industry Co., Ltd. Methods and related devices for optimizing a mobile edge computing (MEC) system
CN107919986A (en) * 2017-11-09 2018-04-17 北京邮电大学 VM migrates optimization method between MEC nodes in super-intensive network
CN108282801A (en) * 2018-01-26 2018-07-13 重庆邮电大学 A kind of switch managing method based on mobile edge calculations
CN108064062A (en) * 2018-02-13 2018-05-22 中国联合网络通信集团有限公司 A kind of method and device of information processing across base station
CN108616816A (en) * 2018-05-07 2018-10-02 重庆邮电大学 A kind of track of vehicle prediction and MEC application moving methods based on limit study
CN108632813A (en) * 2018-05-21 2018-10-09 北京邮电大学 The motion management method and system of mobile edge calculations
CN109391681A (en) * 2018-09-14 2019-02-26 重庆邮电大学 V2X mobility prediction based on MEC unloads scheme with content caching
CN110177379A (en) * 2019-06-03 2019-08-27 中国科学院计算机网络信息中心 Base station access method and system

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111641891A (en) * 2020-04-16 2020-09-08 北京邮电大学 Task peer-to-peer unloading method and device in multi-access edge computing system
CN111641891B (en) * 2020-04-16 2021-11-23 北京邮电大学 Task peer-to-peer unloading method and device in multi-access edge computing system
CN112788109A (en) * 2020-12-29 2021-05-11 哈尔滨工业大学 Service migration method and system based on mobile prediction and multi-layer service deployment
CN112788109B (en) * 2020-12-29 2022-04-19 哈尔滨工业大学 Service migration method and system based on mobile prediction and multi-layer service deployment
CN114217881A (en) * 2022-02-23 2022-03-22 北京航空航天大学杭州创新研究院 Task unloading method and related device
CN114756367A (en) * 2022-04-15 2022-07-15 中国电信股份有限公司 Service migration method, device, medium and electronic equipment
CN114756367B (en) * 2022-04-15 2024-02-23 中国电信股份有限公司 Service migration method, device, medium and electronic equipment
CN115033371A (en) * 2022-08-11 2022-09-09 湖南大学无锡智能控制研究院 Method, equipment and system for service migration in vehicle network

Similar Documents

Publication Publication Date Title
CN110933609A (en) Service migration method and device based on dynamic environment perception
US10231102B2 (en) Techniques for mobility-aware dynamic service placement in mobile clouds
Xia et al. Cost-effective app data distribution in edge computing
US20230016595A1 (en) Performing a handover procedure
CN105009475B (en) In view of the ambulant method and system predicted for admission control and Resource Availability of user equipment (UE)
US20160373936A1 (en) Systems and methods for placing virtual serving gateways for mobility management
WO2018000991A1 (en) Data balancing method and device
CN114157337B (en) Low-orbit satellite inter-satellite switching prediction method based on time-varying graph
CN112148492B (en) Service deployment and resource allocation method considering multi-user mobility
WO2020125539A1 (en) Node device selecting method and related device thereof
Banaie et al. Load-balancing algorithm for multiple gateways in Fog-based Internet of Things
CN112422644A (en) Method and system for unloading computing tasks, electronic device and storage medium
US9560127B2 (en) Systems, methods and algorithms for logical movement of data objects
Xu et al. PDMA: Probabilistic service migration approach for delay‐aware and mobility‐aware mobile edge computing
US20160269297A1 (en) Scaling the LTE Control Plane for Future Mobile Access
Yao et al. Forecasting assisted VNF scaling in NFV-enabled networks
CN113076177A (en) Dynamic migration method of virtual machine in edge computing environment
CN109327340B (en) Mobile wireless network virtual network mapping method based on dynamic migration
Liu et al. Mobility-aware dynamic service placement for edge computing
CN110912999A (en) Service migration method and device based on Markov decision
KR101924628B1 (en) Apparatus and Method for controlling traffic offloading
Liu et al. A QoS-guaranteed online user data deployment method in edge cloud computing environment
JP5575271B2 (en) Method for controlling resource usage within a communication system
CN111465057B (en) Edge caching method and device based on reinforcement learning and electronic equipment
Haung A qoe-aware strategy for supporting service continuity in an mcc environment

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20200327