CN112867088B - Dynamic adjustment method and system for cloud-edge-end communication architecture - Google Patents
Dynamic adjustment method and system for cloud-edge-end communication architecture Download PDFInfo
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- H—ELECTRICITY
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- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses a dynamic adjustment method and a system of a cloud-edge-end communication architecture, wherein the method comprises the following steps: according to the software defined network and the edge computing architecture, a network architecture based on 'cloud-edge-end' is constructed; partitioning a wireless communication network based on a cloud-edge-end network architecture, and calculating the energy consumption of all terminal nodes in a partition; under the condition that the wireless communication network is in normal communication, dynamic energy consumption adjustment of an access node path is carried out according to the energy consumption of all terminal nodes in the subarea; the wireless communication network based on the software defined network constructs a data dynamic energy consumption adjusting scheme according to the distance between a terminal node and an access node and the dynamic energy consumption of an access node path. The communication data energy consumption is calculated by considering the distance between the terminal node and the access node and the dynamic energy consumption of the access node path, and the communication path is re-planned according to the energy consumption, so that the wireless communication network can communicate with lower energy consumption and time delay.
Description
Technical Field
The invention relates to the technical field of mobile communication, in particular to a dynamic adjustment method and a dynamic adjustment system for a cloud-edge-end communication architecture.
Background
Due to high flexibility, expandability and high ratio of cloud computing, cloud computing technology is widely applied, but with the development of mobile internet, such as the rise of AR, VR, high-definition video and real-time services, a centralized cloud computing architecture faces a huge challenge; cloud servers are typically deployed at locations far from end users, and as the number of users increases, the cloud computing network bandwidth will be severely insufficient and less robust, and thus, it is difficult for the cloud computing network architecture to meet the user's demands for low-latency and high-reliability services. With the continuous development of mobile internet, 5G and internet of things, people acquire resources and services in a network through various novel wireless terminal devices, the data volume of access devices is increased, with the continuous increase of various types of the access devices, the service types must be synchronously upgraded, and under the application requirements of the internet of things such as deep perception, intercommunication interconnection, intelligent processing, instant positioning, map construction and augmented reality, the traditional service architecture of an intelligent terminal-internet-cloud computing center is difficult to adapt to the requirement of delay-sensitive application.
Accordingly, mobile Edge Computing (MEC) technology provides a technology for providing information services and cloud Computing resources at a radio access network base station adjacent to a Mobile terminal; software Defined Networking (SDN) provides network programmability, realizes flexible and dynamic network resource management through network function abstraction, and realizes network measurement and control. The MEC-SDN system deploys computing resources, storage resources and network resources to the edge of the Internet closer to the user, so that the resource acquisition speed of the user and the terminal is improved, and the network resources, the computing resources and the storage resources are synchronized by combining the computing resources and the storage resources; in future mobile internet networks, users obtain various resources from a locally proximate MEC-SDN system server, including mobile edge computing-managed computing resources, storage resources, and SDN-managed network resources. Research on mobile edge computing is mainly focused on hardware and architecture, mobile edge computing server deployment, resource virtualization, load balancing, application layer protocols and related field applications.
The research of MEC systems currently suffers from the following drawbacks: many studies show energy efficiency evaluation schemes in specific fields, but the energy efficiency evaluation schemes are only limited to energy efficiency evaluation of the MEC server, and the SDN network and the cloud computing center are not taken into consideration. The limited scheme cannot be used for modeling and analyzing cross-layer application simultaneously applying MEC service and cloud computing service; a system energy efficiency evaluation system with 'completeness, consistency and high efficiency' based on a mobile terminal, edge computing and cloud computing architecture is not provided; most of the existing research work simplifies the problem of energy efficiency dynamic change in the terminal moving process, and only the energy consumption of data transmission between the mobile terminal and the edge computing server under a static condition at a certain moment is considered. For a wireless communication network based on cloud computing and the defects, the problems of high delay and high energy efficiency from a traditional mobile terminal to a cloud computing platform exist.
Disclosure of Invention
Therefore, the dynamic adjustment method and the dynamic adjustment system for the cloud-edge-end communication architecture provided by the invention overcome the defects of high delay and high energy efficiency from the traditional mobile terminal to the cloud computing platform in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme:
in a first aspect, an embodiment of the present invention provides a method for dynamically adjusting a "cloud-edge-end" communication architecture, including:
according to the software defined network and the edge computing architecture, a network architecture based on 'cloud-edge-end' is constructed;
partitioning a wireless communication network based on a cloud-edge-end network architecture, and calculating the energy consumption of all terminal nodes in a partition;
under the condition that the wireless communication network is in normal communication, dynamic energy consumption adjustment of an access node path is carried out according to the energy consumption of all terminal nodes in the subarea;
the wireless communication network based on the software defined network constructs a data dynamic energy consumption adjusting scheme according to the distance between a terminal node and an access node and the dynamic energy consumption of an access node path.
In one embodiment, the terminal node comprises: common nodes, partition nodes; under the support of a software defined network architecture, terminal nodes in a network are divided, a clustering mechanism is utilized to select partial nodes in the terminal nodes as partition nodes, and data are forwarded through the partition nodes.
In one embodiment, the partition division is performed according to the distance between the terminal node and the edge calculation access node and the residual energy of the terminal node, and the energy consumption of all the terminal nodes in the partition is calculated.
In one embodiment, the energy consumption of the transmission length l of the end node in the partition is calculated by the following formula:
wherein l r 、l f Respectively representing the length of data in a convergence partition of a partition node in a partition node i and the length of data in other partitions in fusion forwarding j Indicating the length of data sent by the regular terminal node to the partition node, d i A partition node distance, d, representing the distance of partition node i from the next hop j Denotes the distance, ε, of the common end node to the partition node fs Respectively representing the signal fading coefficients, epsilon, of the signals propagating in free space fs And epsilon mp Respectively, the free space propagation attenuation coefficient and the multipath propagation attenuation coefficient, P, of the signal r Energy consumption for receiving single byte data.
In an embodiment, in a wireless communication network based on an SDN architecture, a data forward transmission path is not unique, and an SDN controller completes dynamic energy consumption adjustment of an access node path according to the size of data volume to be forwarded by a partition node and the remaining energy of the partition node.
In one embodiment, the energy consumption of partition i is calculated by the following equation:
wherein, P Ai (l, d) represents the energy consumption of each partition node in partition i,
represents the sum of the energy consumption of the common nodes in the partition j for transmitting data.
In one embodiment, the wireless communication network communicates normally, comprising: maximum communication radius R of partitioned node CH Not less than the maximum communication radius R of the common node node Is preset multiple of.
In a second aspect, an embodiment of the present invention provides a dynamic adjustment system for a "cloud-edge-end" communication architecture, including:
the cloud-edge-end network architecture building module is used for building a cloud-edge-end-based network architecture according to a software defined network and an edge computing architecture;
the energy consumption calculation module is used for partitioning the wireless communication network based on the cloud-edge-end network architecture and calculating the energy consumption of all terminal nodes in the partition;
the dynamic energy consumption adjusting module is used for adjusting the dynamic energy consumption of the access node path according to the energy consumption of all terminal nodes in the subarea under the condition of normal communication of the wireless communication network;
and the adjusting scheme generating module is used for constructing a data dynamic energy consumption adjusting scheme based on a wireless communication network of the software defined network according to the distance between the terminal node and the access node and the dynamic energy consumption of the access node path.
In a third aspect, an embodiment of the present invention provides a terminal, including: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so as to cause the at least one processor to perform the method for dynamically adjusting a "cloud-edge-end" communication architecture according to the first aspect of the embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer instructions are configured to enable the computer to execute the method for dynamically adjusting a "cloud-edge-end" communication architecture according to the first aspect of the embodiment of the present invention.
The technical scheme of the invention has the following advantages:
according to the dynamic adjustment method and the dynamic adjustment system for the cloud-edge-end communication architecture, a network architecture based on the cloud-edge-end is constructed according to a software defined network and an edge computing architecture; partitioning a wireless communication network based on a cloud-edge-end network architecture, and calculating the energy consumption of all terminal nodes in a partition; under the condition that the wireless communication network is in normal communication, dynamic energy consumption adjustment of an access node path is carried out according to the energy consumption of all terminal nodes in the subarea; the wireless communication network based on the software defined network constructs a data dynamic energy consumption adjusting scheme according to the distance between a terminal node and an access node and the dynamic energy consumption of an access node path. The communication data energy consumption is calculated by considering the distance between the terminal node and the access node and the dynamic energy consumption of the access node path, and the communication path is re-planned according to the energy consumption, so that the wireless communication network can communicate with lower energy consumption and time delay.
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, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of a dynamic adjustment method of a "cloud-edge-end" communication architecture according to an embodiment of the present invention;
fig. 2 is a diagram of a "cloud-edge-end" wireless communication network architecture based on SDN, which is a specific example of a dynamic adjustment method for a "cloud-edge-end" communication architecture according to an embodiment of the present invention;
fig. 3 is an MEC architecture diagram of a wireless communication network according to a specific example of a dynamic adjustment method of a "cloud-edge-end" communication architecture provided in an embodiment of the present invention;
fig. 4 is an application scenario diagram of a specific example of a dynamic adjustment method of a "cloud-edge-end" communication architecture according to an embodiment of the present invention;
fig. 5 is a schematic view of a wireless communication network partition of a specific example of a dynamic adjustment method of a "cloud-edge-end" communication architecture according to an embodiment of the present invention;
fig. 6 is a simulation comparison diagram of response delay of services without request amount according to an embodiment of the present invention;
FIG. 7 is a comparison diagram of simulation of system energy consumption without request amount according to an embodiment of the present invention;
fig. 8 is a block diagram of a dynamic adjustment system of a "cloud-edge-end" communication architecture according to an embodiment of the present invention;
fig. 9 is a composition diagram of a specific example of a terminal according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1
The dynamic adjustment method for the cloud-edge-end communication architecture provided by the embodiment of the invention, as shown in fig. 1, includes the following steps:
step S1: according to the software defined network and the edge computing architecture, a network architecture based on cloud-edge-end is constructed.
In the embodiment of the present invention, according to a Mobile Edge Computing (MEC) architecture and a Software Defined Network (SDN) architecture, a switch and a controller of an SDN are integrated into the MEC architecture, so as to implement an SDN-MEC architecture. As shown in fig. 2, a "cloud-edge-end" wireless communication network architecture system based on SDN is constructed, and the specific process is as follows: the SDN system structure consists of an application layer, a control layer and a data transmission layer; the control layer and the data transmission layer are connected through an SDN southbound interface, an OpenFlow communication protocol is adopted, and each edge element in the data transmission layer has a uniform communication identifier, such as: the switch and the AP are merely examples, and not limited thereto, and in practical application, the corresponding edge element is selected according to actual requirements. As shown in fig. 3, an edge cloud framework in a wireless communication network is mainly composed of an MEC, an edge access device, a mobile intelligent terminal, and a cloud data center. The deployment of the MEC equipment is one of main differences between a cloud-edge-end architecture and a traditional cloud computing architecture, terminal nodes in a network are divided under the support of an SDN architecture, then a clustering mechanism is utilized to select partial nodes in the terminal nodes as partition nodes, and data are forwarded through the partition nodes, so that the energy consumption of common terminal nodes is reduced. Fig. 4 is a diagram of an application scenario of a wireless cloud edge network based on an SDN.
In one embodiment, the simulation environment is built using an SDN virtual environment consisting of Floodlight and Mininet, the simulation environment is a PC with a 2.6GHz CPU and 8GB RAM, and the software environment is a 64-bit ubuntu16.04 operating system with Floodlight, mininet and Iperf simulation tools. The flodlight is a current mainstream SDN controller, and has stable and easily and flexibly controlled performance of the SDN network. Writing an application program to call RESTful API of Floodlight to form an application layer, building a network facility by using an MEC framework to form a communication layer, and accessing terminal equipment to an OpenFlow switch to form a node layer.
Step S2: and partitioning the wireless communication network based on the cloud-edge-end network architecture, and calculating the energy consumption of all terminal nodes in the partitions.
In the embodiment of the present invention, as shown in fig. 5, the wireless communication network is partitioned, nodes in the partition are clustered, and a terminal node of a suitable point is selected as a partition node, and other nodes are ordinary nodes, so that energy consumption of various nodes in the partition is calculated. The distribution of the terminal nodes is uneven, and the energy consumption of data transmission of different terminal nodes is different, so that in a cloud-edge-end network architecture based on the SDN, the distance between the terminal nodes and the edge is calculated, the remaining energy of the terminal nodes is partitioned, and the terminal nodes in the partitions are selected. The wireless communication network is divided into n areas, each area comprises a common node and a partition node, a node which gathers terminal node data in the coverage area of the node in the partition is called a partition node, and other terminal nodes which collect data and forward the data to the area nodes are called common nodes. The partition nodes converge data collected by common terminal nodes in the coverage range, fuse the data received by the common terminal nodes and data forwarded by other partitions, transmit the data to next-hop partition nodes, and transmit the data to the edge computing nodes and the cloud computing data center in a multi-hop mode for further analysis and processing.
In the embodiment of the present invention, based on a "cloud-edge-end" network architecture of an SDN architecture, a wireless communication network and the "cloud-edge" network are connected to each other through an edge computing node, where a wireless communication network in which a network access node with an edge computing device is located is partitioned into a 1 st area, and an area farthest from the edge computing node is referred to as a tail area; the process of data transmission from the tail zone to the 1 st zone to the edge computing access node is called forward transmission. In a distributed wireless communication network, the energy consumption of forward transmission between the 1 st area and the tail area varies with the change of the subarea; in addition, the transmission function between the common node and the partitioned node is related to the distance between the common node and the partitioned node and the size of the transmission data volume, so that in the wireless communication network based on the SDN, the energy consumption of the network can be dynamically adjusted by changing the transmission path of the data in the wireless network.
After the wireless communication network is subjected to area division and clustering, the partition nodes converge the data of other terminal nodes in the area and forward the data to the partition node processes of other partitions for forward transmission. The energy consumption of each partition node in the partition i mainly comprises two parts: energy consumption (P) for receiving normal node data packet Rx ) And energy consumption (P) for merging forwarding data packets Tx )。
Wherein l r 、l f Respectively representing the length of the data in the aggregation partition of the partition node in the partition node i and the length of the data of other partitions in the fusion forwarding mode. Epsilon represents the signal fading coefficient of the signal propagating in the space, and the value is epsilon fs Or epsilon mp ；P r Is a constant representing the energy consumption for receiving the single byte data; d is a radical of i Representing the partition node distance from the partition node i to the next hop; delta represents the transmission energy consumption of the node and the signal space propagation attenuation index, the value is 2 or 4, only by way of example, but not by way of limitation, and in practical application, a corresponding numerical value is selected according to actual requirements; d 0 The threshold point for a transition of the transmission scheme of a signal in space is usually set to a value of [75,80 ]]Within the range of rice. Epsilon fs And epsilon mp Are respectively 13.5pJ/bit/m 2 And 0.0015pJ/bit/m 4 。
The energy consumption of the ordinary node for transmitting data is expressed as follows:
wherein l j Representing the length of data sent by the common node to the partition node; d j Representing the distance from the common node to the partition node; epsilon fs Respectively representing the signal fading coefficients of the signals propagated in free space; epsilon fs And ε mp Respectively, the free-space propagation attenuation coefficient and the multipath propagation attenuation coefficient of the signal.
And step S3: and under the condition that the wireless communication network is in normal communication, dynamically adjusting the energy consumption of the access node path according to the energy consumption of all the terminal nodes in the subarea.
In the embodiment of the invention, in each area, no matter which wireless forward transmission link the terminal node of the wireless network sends the data to the edge computing network, the access node of the edge computing network receives the dataThe amounts are all the same. In a wireless communication network based on an SDN architecture, an SDN controller collects terminal and link information of the network to construct a global view of the network, so that the network is controlled from the global perspective. In each area, in order to ensure that all terminal nodes in the wireless network can be stably accessed into the edge computing network, the maximum communication radius R of each partition node CH Not less than the maximum communication radius R of the common node node Is selected according to actual requirements, e.g. the maximum communication radius R of a partition node CH Not less than the maximum communication radius R of the common node node 2 times of (i.e. taking into account R) CH ≥2R node . Under the condition that normal communication of the network is ensured, the partition nodes transmit the converged data to the access nodes of the edge computing by selecting different paths for further processing and computing. In each partition, a larger partition number indicates that the partition is farther from the access node of the edge calculation, and the more energy is consumed in the data transmission process.
In a wireless communication network based on an SDN architecture, a data forward transmission path is not unique, and an SDN controller dynamically adjusts energy consumption of the wireless communication network according to the size of data amount to be forwarded by a partition node and the remaining energy of the partition node, so that the energy consumption of the partition i can be expressed as:
and the SDN controller completes dynamic energy consumption adjustment of the access node path according to the size of the data volume to be forwarded by the partition node and the residual energy of the partition node.
And step S4: the wireless communication network based on the software defined network constructs a data dynamic energy consumption adjusting scheme according to the distance between a terminal node and an access node and the dynamic energy consumption of an access node path.
In the embodiment of the invention, based on the SDN wireless communication network, the controller dynamically adjusts the transmission path of data, thereby adjusting the energy consumption of data transmission in the network. The number of nodes in the SDN system structure zone is determined by the communication distance of the zone, and network nodes with larger communication distance are relatively fewer; in order to reduce the energy consumption of the SDN-based cloud edge network, a transmission path needs to be dynamically adjusted, so that the energy utilization efficiency is improved. Thus, when energy consumption is high, the communication path is redeployed; when the receiving node is fixed, the sending node selects a shorter path to realize communication, thereby completing dynamic adjustment of the energy consumption of the partition communication distance; the total energy consumption of a network with a total transmission length l in a wireless communication network is as follows:
the total energy consumption of the network can be further expressed as:
wherein l j Representing the length of data sent by the common node to the partition node; d j Representing the distance from the common node to the partition node; epsilon fs Respectively representing the signal fading coefficients of the signals propagated in free space; epsilon fs And ε mp The free space propagation attenuation coefficient and the multipath propagation attenuation coefficient of the signal are respectively; p is r Is a constant that represents the energy consumption for receiving a single byte of data and can be obtained by averaging over multiple measurements.
In the embodiment of the present invention, the method further includes: and calculating transmission in the wireless communication network according to the constructed dynamic energy consumption regulation scheme, and calculating the integral transmission delay of the data by combining edge calculation and cloud calculation to ensure the service quality of the network.
In a traditional cloud computing network, a wireless communication network needs to transmit data to a cloud computing center through a network access node for centralized processing, and not only is the time delay of data processing increased, but also the network energy consumption is increased in the processing; the transmission delay of a signal is expressed by the following equation:
wherein, T i Representing the processing time delay of the data packet in the transmission node, wherein the propagation speed of the signal in the space is equal to the speed of light, and the propagation time delay of the signal in the space is not considered in order to reduce the complexity of calculation; t is a unit of n The processing delay in the terminal node for each data packet can be obtained by statistical calculation.
Without considering the delay, the network reduces the energy consumption mainly by increasing the number of hops, but adding the delay to delay-sensitive applications will greatly reduce the availability of services, and for this reason, the delay problem of data processing is reduced by processing part of the data using edge computing technology, thereby assisting the wireless communication network to reduce the energy consumption of the system. Therefore, the problem of real-time performance of user services is improved under the SDN-MEC network system architecture; in order to reduce the delay of service response, MEC technology is introduced to handle the computation-intensive operations at the edge of the network, and at the same time, SDN technology is introduced to realize centralized control of the network and to collect global information of the network. In an application scenario, consider a software-defined cloud edge computing architecture composed of k MEC devices, whose network topology is represented using G = (V, E), where V is a set of nodes and E is an edge set. Thus V = { V = 1 ,v 2 ,...,v k S, C }, wherein v i The method comprises the following steps that MEC equipment is adopted, k is the number of the equipment, S is an SDN controller, and C is a cloud computing service platform; edge set availability
Representing; />
Representing a node v i And v j A communication link between; />
Representing a node v i And v j The delay of (2).
In the process of executing the service, the service received by the MEC equipment is firstly divided into a plurality of subtasks and satisfies Task i ＝δ i Task, wherein δ i The proportion of the subtasks in the total Task is taken as the ratio, and then the Task is unloaded into each subtask and is processed by the MEC equipment. The preprocessing result Task pre The method includes the steps that a MEC carries out decision-making locally or sends the MEC to a cloud computing service platform, since service response delay in distributed computing is equal to the maximum processing delay of all subtasks, performance needs to be considered preferentially in order to guarantee performance and service quality of a network when a user is served, and therefore the overhead of network energy consumption needs to be reduced under the condition that the requirement of the user on transmission delay is met, and the total service response delay in an SDN-MEC network architecture is expressed as follows:
wherein, the first and the second end of the pipe are connected with each other,
for MEC equipment v i Neutron Task i Calculated time of (d) () i The coefficients are assigned to the best task,
representing a node v i And v j Is delayed,. Sup.>
Representing a node v i And v j The subtask allocation relationship of (1); when m =1, the subtask assignment relationship exists, and when m =0, the subtask assignment relationship does not exist; />
Delay representing matching and identifying pre-processing results on the cloud; />
Indicates that the pretreatment is to be performedResulting in communication delay when sent to the cloud server.
In order to optimize and minimize the delay of traffic response, an optimal set of task assignment coefficients δ is required i The service response delay based on the SDN-MEC network architecture can be expressed as:
wherein, delta i Coefficients are assigned to the optimal tasks.
Representing a node v i And v j The subtask allocation relationship of (1). In the SDN-MEC architecture, service data are preprocessed through edge nodes to reduce data transmission delay, so that the problem of delay increase caused by energy consumption reduction in a wireless communication network is solved, and the increased energy consumption of the wireless communication network is reduced while the network service quality is ensured.
By comparison: the network energy consumption and time delay indexes of the SDN-MEC scheme, the traditional cloud computing scheme and the MEC scheme without edge adjustment. In the simulation, MEC device v1 is selected as a single MEC device. As shown in fig. 6, without using the simulation result of response delay of services in the number of requests, when the number of user requests is less than 10, the delay of the SDN-MEC scheme is less than that of the cloud computing scheme and the single MEC device scheme, but the delay difference of the three schemes is not large; but as the number of users increases, the processing delay in the network also increases.
In one embodiment, as shown in FIG. 7, rather than requiring system power consumption in the number of requests, power consumption in the network is continually increasing as the number of users increases in the simulation environment. With the increase of the number of users, the energy consumption of the wireless transmission nodes in the system for processing data is also increased continuously, especially the energy consumption of the nodes farthest from the edge computing node is also increased, and the change trend of the rapid increase of the energy consumption with the increase of the number of the user requests in the graph also illustrates the problem. By comparing three different transmission schemes, and referring to fig. 6, it can be concluded that the scheme provided in the embodiment of the present invention can reduce the overall energy consumption of the wireless communication network while adjusting the transmission delay, and also shows the effectiveness of the embodiment of the present invention.
The dynamic adjustment method of the cloud-edge-end communication architecture provided by the embodiment of the invention comprises the following steps of constructing a network architecture based on a cloud-edge-end according to a software defined network and an edge computing architecture; partitioning a wireless communication network based on a cloud-edge-end network architecture, and calculating the energy consumption of all terminal nodes in a partition; under the condition that the wireless communication network is in normal communication, dynamic energy consumption adjustment of an access node path is carried out according to the energy consumption of all terminal nodes in a subarea; the wireless communication network based on the software defined network constructs a data dynamic energy consumption adjusting scheme according to the distance between a terminal node and an access node and the dynamic energy consumption of an access node path. The communication data energy consumption is calculated by considering the distance between the terminal node and the access node and the dynamic energy consumption of the access node path, and the communication path is re-planned according to the energy consumption, so that the wireless communication network can communicate with low energy consumption and time delay.
Example 2
An embodiment of the present invention provides a dynamic adjustment system of a "cloud-edge-end" communication architecture, as shown in fig. 8, including:
the cloud-edge-end network architecture building module 1 is used for building a cloud-edge-end-based network architecture according to a software defined network and an edge computing architecture; this module executes the method described in step S1 in embodiment 1, and is not described herein again.
The energy consumption calculation module 2 is used for partitioning the wireless communication network based on the cloud-edge-end network architecture and calculating the energy consumption of all terminal nodes in the partition; this module executes the method described in step S2 in embodiment 1, and is not described herein again.
The dynamic energy consumption adjusting module 3 is used for adjusting the dynamic energy consumption of the access node path according to the energy consumption of all terminal nodes in the subarea under the condition that the wireless communication network is in normal communication; this module executes the method described in step S3 in embodiment 1, which is not described herein again.
The adjusting scheme generating module 4 is used for constructing a data dynamic energy consumption adjusting scheme based on a wireless communication network of a software defined network according to the distance between the terminal node and the access node and the dynamic energy consumption of the access node path; this module executes the method described in step S4 in embodiment 1, which is not described herein again.
The embodiment of the invention provides a dynamic regulation system of a 'cloud-edge-end' communication architecture, and provides a network architecture based on a 'cloud-edge-end' which is constructed according to a software defined network and an edge computing architecture; partitioning a wireless communication network based on a cloud-edge-end network architecture, and calculating the energy consumption of all terminal nodes in a partition; under the condition that the wireless communication network is in normal communication, dynamic energy consumption adjustment of an access node path is carried out according to the energy consumption of all terminal nodes in the subarea; the wireless communication network based on the software defined network constructs a data dynamic energy consumption adjusting scheme according to the distance between a terminal node and an access node and the dynamic energy consumption of an access node path. The communication data energy consumption is calculated by considering the distance between the terminal node and the access node and the dynamic energy consumption of the access node path, and the communication path is re-planned according to the energy consumption, so that the wireless communication network can communicate with low energy consumption and time delay.
Example 3
An embodiment of the present invention provides a terminal, as shown in fig. 9, including: at least one processor 401, such as a CPU (Central Processing Unit), at least one communication interface 403, memory 404, and at least one communication bus 402. Wherein a communication bus 402 is used to enable the connection communication between these components. The communication interface 403 may include a Display (Display) and a Keyboard (Keyboard), and the optional communication interface 403 may also include a standard wired interface and a standard wireless interface. The Memory 404 may be a high-speed RAM Memory (Random Access Memory) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The memory 404 may optionally be at least one memory device located remotely from the processor 401. Wherein the processor 401 may execute the dynamic adjustment method of the "cloud-edge-end" communication architecture in embodiment 1. A set of program codes is stored in the memory 404, and the processor 401 calls the program codes stored in the memory 404 for executing the dynamic adjustment method of the "cloud-edge-end" communication architecture in embodiment 1. The communication bus 402 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus 402 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one line is shown in FIG. 9, but this does not represent only one bus or one type of bus. The memory 404 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: non-volatile memory), such as a flash memory (english: flash memory), a hard disk (english: hard disk drive, abbreviated: HDD) or a solid-state drive (english: SSD); the memory 404 may also comprise a combination of the above types of memory. The processor 401 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of a CPU and an NP.
The memory 404 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: flash memory), such as a Hard Disk Drive (HDD) or a solid-state drive (SSD); the memory 404 may also comprise a combination of the above types of memory.
The processor 401 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of a CPU and an NP.
The processor 401 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), a General Array Logic (GAL), or any combination thereof.
Optionally, the memory 404 is also used to store program instructions. The processor 401 may call a program instruction to implement the dynamic adjustment method of the "cloud-edge-end" communication architecture in embodiment 1.
The embodiment of the present invention further provides a computer-readable storage medium, where computer-executable instructions are stored on the computer-readable storage medium, and the computer-executable instructions may execute the dynamic adjustment method of the "cloud-edge-end" communication architecture in embodiment 1. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. This need not be, nor should it be exhaustive of all embodiments. And obvious variations or modifications of the invention may be made without departing from the spirit or scope of the invention.
Claims (9)
1. A dynamic adjustment method of a cloud-edge-end communication architecture is characterized by comprising the following steps:
according to the software defined network and the edge computing architecture, a network architecture based on 'cloud-edge-end' is constructed;
partitioning a wireless communication network based on a cloud-edge-end network architecture, calculating the energy consumption of all terminal nodes in a partition, and calculating the energy consumption of the terminal nodes in the partition with the transmission length l according to the following formula:
wherein l r 、l f Respectively representing the length of data in a convergence partition of a partition node in a partition node i and the length of data in other partitions in fusion forwarding j Represents the length of data sent by the common node j to the partition node i, d i Indicating the partition node distance, d, of partition node i from the next hop j Denotes the distance, ε, of the common node j to the partition node i fs And epsilon mp Respectively, the free space propagation attenuation coefficient and the multipath propagation attenuation coefficient, P, of the signal r Energy consumption for receiving data in single byte, d 0 A threshold point at which the transmission scheme for the signal transitions in space;
under the condition that the wireless communication network is in normal communication, dynamic energy consumption adjustment of an access node path is carried out according to the energy consumption of all terminal nodes in the subarea;
the wireless communication network based on the software defined network constructs a data dynamic energy consumption adjusting scheme according to the distance between a terminal node and an access node and the dynamic energy consumption of an access node path.
2. The dynamic adjustment method of a "cloud-edge-end" communication architecture of claim 1, wherein the end node comprises: a common node, a partition node; under the support of a software defined network architecture, terminal nodes in a network are divided, a clustering mechanism is utilized to select partial nodes in the terminal nodes as partition nodes, and data are forwarded through the partition nodes.
3. The dynamic adjustment method for a "cloud-edge-end" communication architecture according to claim 1, wherein the energy consumption of all terminal nodes in a partition is calculated by partitioning according to a distance between the terminal node and an edge computing access node and a remaining energy of the terminal node.
4. The method of claim 1, wherein a data forward transmission path is not unique in a wireless communication network based on an SDN architecture, and the SDN controller performs dynamic energy consumption adjustment on an access node path according to a size of a data amount to be forwarded by a partition node and a residual energy of the partition node.
5. The dynamic tuning method of a "cloud-edge-end" communication architecture of claim 4, wherein the energy consumption of partition i is calculated by the following formula:
wherein, P Ai (l, d) represents the energy consumption of each partition node in partition i,
represents the sum of the energy consumption of the common node j in the partition i for transmitting data.
6. The dynamic adjustment method of the "cloud-edge-end" communication architecture of claim 1, wherein the wireless communication network performs normal communication, and comprises: maximum communication radius R of partitioned node CH Not less than the maximum communication radius R of the common node node Is preset multiple of.
7. A system for dynamically adjusting a cloud-edge-end communication architecture, comprising:
the cloud-edge-end network architecture building module is used for building a cloud-edge-end-based network architecture according to a software defined network and an edge computing architecture;
the energy consumption calculation module is used for partitioning a wireless communication network based on a cloud-edge-end network architecture, calculating the energy consumption of all terminal nodes in a partition, and calculating the energy consumption of the terminal nodes with the transmission length of l in the partition according to the following formula:
wherein l r 、l f Respectively representing the length of data in a zone node convergence zone and the length of data of other zones in fusion forwarding in the zone node i, l j Represents the length of data sent by the common node j to the partition node i, d i A partition node distance, d, representing the distance of partition node i from the next hop j Denotes the distance, ε, from the common node j to the partition node i fs And epsilon mp Respectively, the free space propagation attenuation coefficient and the multipath propagation attenuation coefficient, P, of the signal r Energy consumption for receiving data in single byte, d 0 A threshold point at which the transmission scheme for the signal transitions in space;
the dynamic energy consumption adjusting module is used for adjusting the dynamic energy consumption of the access node path according to the energy consumption of all terminal nodes in the subarea under the condition that the wireless communication network is in normal communication;
and the adjusting scheme generating module is used for constructing a data dynamic energy consumption adjusting scheme based on a wireless communication network of the software defined network according to the distance between the terminal node and the access node and the dynamic energy consumption of the access node path.
8. A terminal, comprising: at least one processor, and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to cause the at least one processor to perform the method of dynamically adjusting a cloud-edge-end communication architecture of any of claims 1-6.
9. A computer-readable storage medium storing computer instructions for causing a computer to perform the method for dynamically adjusting a cloud-edge-to-end communication architecture according to any one of claims 1 to 6.
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