CN112312504A - Cross-domain fusion switching method for heterogeneous network - Google Patents

Cross-domain fusion switching method for heterogeneous network Download PDF

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CN112312504A
CN112312504A CN202011278601.0A CN202011278601A CN112312504A CN 112312504 A CN112312504 A CN 112312504A CN 202011278601 A CN202011278601 A CN 202011278601A CN 112312504 A CN112312504 A CN 112312504A
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network
data
wireless
attribute data
service
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王炜发
徐艳
张建丰
章广梅
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Seventh Research Institute Of China Electronics Technology Group Corp
CETC 7 Research Institute
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H04W36/0058—Transmission of hand-off measurement information, e.g. measurement reports
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H04W36/0066—Transmission or use of information for re-establishing the radio link of control information between different types of networks in order to establish a new radio link in the target network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0083—Determination of parameters used for hand-off, e.g. generation or modification of neighbour cell lists
    • H04W36/00835—Determination of neighbour cell lists
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0083—Determination of parameters used for hand-off, e.g. generation or modification of neighbour cell lists
    • H04W36/0085—Hand-off measurements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/14—Reselecting a network or an air interface
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/16—Performing reselection for specific purposes
    • H04W36/22—Performing reselection for specific purposes for handling the traffic

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Abstract

The invention provides a heterogeneous network cross-domain fusion switching method, which comprises the following steps: s1: the method comprises the following steps that a mobile terminal accessed to a heterogeneous network carries out self-adaptive scanning on a current accessed wireless network and surrounding wireless networks and uploads collected data to a wireless access point; s2: each wireless access point in the control range of the centralized hub node periodically measures network attribute data in the range and uploads the network attribute data to the centralized hub node; s3: the centralized hub node performs service perception according to data uploaded by the wireless access point and performs switching prejudgment; s4: the centralized hub node performs service quality perception according to the network attribute data in the available network list, and selects the optimal network from the rest networks for switching; s5: the centralized hub node periodically measures the attribute data of the current connection network, and if the performance meets the requirement, the centralized hub node is maintained unchanged, otherwise, the centralized hub node returns to the step S1 for execution.

Description

Cross-domain fusion switching method for heterogeneous network
Technical Field
The invention relates to the technical field of communication, in particular to a cross-domain fusion switching method for a heterogeneous network.
Background
With the development of communication technology, various wireless access technologies are developed, so that a new scene that a plurality of wireless networks coexist is generated. In this scenario, the user needs to perform vertical handover in multiple wireless networks, and needs a heterogeneous vertical handover technology to ensure normal communication. Heterogeneous vertical handovers mainly include three phases: a network discovery phase, a handover decision phase and a handover execution phase.
In the network discovery phase, a user can search for a network accessible to the user in a heterogeneous wireless network area, and in the process, the discovery time of the network and the energy consumption of a terminal need to be balanced. The shorter the network discovery time is, the more likely the user is to switch to a proper network early, and the QoS of the user is guaranteed. However, keeping the user listening to the network at a high frequency all the time results in a significant increase in the terminal power consumption. Therefore, the balance between the network discovery time and the terminal power consumption needs to be considered.
The switching decision stage decides whether the user needs to switch, which network to switch to and the switching initiation opportunity, which are closely related to the QoS of the user. The vertical handover of the heterogeneous wireless network is different from that of the homogeneous network, and the handover decision needs to be comprehensively carried out by considering the service requirement of the user and the complex network environment.
As shown in fig. 1, it is a general flow chart of the current handover algorithm, and the existing vertical handover algorithm includes: vertical Handover Algorithm [ 1 ] Dhar Roy, S.And S.R.Vamshiddar reset.Signal Strength Ratio Based Vertical Handoff Decision Algorithm in integrated Heterogeneous Networks [ J ]. Wireless Personal Communications,2014,77(4): 2565-; 【3】 Falowo O E, Chan H A. RAT selection for multiple wells in heterologous networks using modified topsis group resolution technique [ C ]// IEEE International Symposium ON Personal index & Mobile Radio Communications, Toronto, ON, Canada,2011: 1371-; 【4】 Falowo O E, Chan H A. RAT selection for multiple wells in heterologous networks using modified top sizing group calculation technique [ C ]// IEEE International Symposium ON Personal index & Mobile Radio Communications, Toronto, ON, Canada,2011: 1371-. Different types of wireless access points in the heterogeneous network have different powers, and ping-pong effect can be generated by directly using the received signal power as a handover decision. Document [ 1 ] attenuates the effect of received signal power fluctuations on handover by introducing dwell times and hysteresis levels, but may not allow the user to switch to the optimal network in a timely manner.
In the prior art, a fixed scanning period is set as a basic method for the size of a network scanning period in a network discovery phase, and in some improvement schemes, the size of the received signal power is used for adjusting the scanning period. However, this method has the following disadvantages:
in the network discovery phase, a fixed scanning period is set or the scanning period is set by solely using the power of the received signal, so that the network discovery time and the terminal energy consumption cannot be balanced. If the network scanning period is too small, although the available wireless networks around can be found in time, the energy consumption of the terminal is high due to the large number of network discovery times; on the contrary, if the scanning period of the network is too long, the terminal cannot find an available wireless network in time, and the network experience of the user is affected.
In the stage of switching judgment, the traditional multi-attribute decision algorithm only considers the subjective weight of an analytic hierarchy process or the objective weight of an entropy weight method. The objective attribute weight of the network cannot be reflected or the preference of a decision maker for different network attributes cannot be reflected, and the real-time condition of the network cannot be accurately judged by considering the subjective weight only according to different service types and different network attributes; meanwhile, if only the objective weight is considered, the attribute characteristics of the network cannot be reflected.
Disclosure of Invention
The invention provides a cross-domain fusion switching method for a heterogeneous network, aiming at overcoming the problems that the prior art cannot find available new networks in time, network discovery delay is caused, and switching efficiency is reduced.
In order to solve the technical problems, the technical scheme of the invention is as follows: a heterogeneous network cross-domain fusion switching method comprises the following steps:
s1: the method comprises the following steps that a mobile terminal accessed to a heterogeneous network carries out self-adaptive scanning on a current accessed wireless network and surrounding wireless networks and uploads collected data to a wireless access point;
s2: each wireless access point in the control range of the centralized hub node periodically measures network attribute data in the range and uploads the network attribute data to the centralized hub node;
s3: the centralized hub node performs service perception according to data uploaded by the wireless access point and performs switching prejudgment;
s4: the centralized hub node performs service quality perception according to the network attribute data in the available network list, and selects the optimal network from the rest networks for switching;
s5: the centralized hub node periodically measures the network attribute data of the currently connected network, and if the performance meets the requirement, the network attribute data is maintained unchanged, otherwise, the operation returns to the step S3 for execution.
Preferably, the specific steps of step S1 are as follows:
s101: collecting link characteristics and service attributes of the mobile terminal in a currently connected wireless network, and the signal strength and the moving speed received by the mobile terminal;
s102: performing first preprocessing on the collected data, wherein the first preprocessing comprises but is not limited to removing abnormal values in original data and filling missing values, so as to realize data cleaning;
s103: adaptively setting a scanning period according to the data after the first preprocessing;
s104: scanning a currently connected wireless network and surrounding wireless networks according to a set scanning period;
s105: step 102 and step 104 are repeated, and the scanned available network set is N ═ N-1，N2，...，NlAnd l represents the number of available wireless networks scanned by the mobile terminal.
Further, in step S2, the specific steps are as follows:
s201: each wireless access point collects network attribute data in the coverage range of each wireless access point, wherein the network attribute data comprises but is not limited to available bandwidth, throughput, time delay, jitter and packet loss rate;
s202: performing second preprocessing on the collected network attribute data, wherein the second preprocessing comprises but is not limited to removing abnormal values and filling missing values in the network attribute data, so that data cleaning is realized;
s203: processing the second preprocessed data, calculating according to a corresponding attribute index calculation formula, and uploading the data together with other attribute data in a centralized manner;
s204: and uploading the processed network attribute data and the data collected by the mobile equipment connected with the processed network attribute data to the centralized hub node.
Still further, in step S3, the specific steps are as follows:
s301: the centralized hub node establishes a service perception information base according to the service type and corresponding service data formulated by the 3 GPP; the service types comprise a session type, a streaming media type, an interaction type and a background type; the service perception information base comprises different specific port numbers corresponding to different service types;
s302: sensing the service type of the mobile terminal by using the uploaded specific port number, and finding the service type and service data corresponding to the port number in a service sensing information base;
s303: comparing the perceived service type and the corresponding service data with the network attribute data in the available network set N; if all the network attribute data meet the data requirements in the service perception information base, the wireless network is continuously reserved in the available network set; if one or more of the available networks are not accordant, the wireless network number is deleted from the available network set, and the rest available network set is represented as
Figure BDA0002779977090000044
Figure BDA0002779977090000043
Where n represents the number of available wireless networks.
Still further, in step S4, the specific steps are as follows:
401: determining a subjective weight matrix of a reference network attribute under different service types according to different service types formulated in 3 GPP;
s402: determining an objective weight matrix by using actual network attribute data uploaded by each wireless access point;
s403: calculating a comprehensive weight value by using a subjective weight value matrix and an objective weight value matrix through a set weighting factor;
s404: and (4) obtaining the utility value of each wireless network by using a weighting method according to the comprehensive weight value obtained in the step (S403), if the maximum utility value in the alternative wireless network is equal to the utility value of the current access wireless network or the ratio of the maximum utility value to the utility value is less than a set threshold value, the mobile terminal stays in the current access wireless network, and otherwise, the wireless network with the maximum utility value is selected as the access network for switching.
Still further, in step S401, specifically,
d1: determining reference attributes selected by a network, wherein the reference attributes include but are not limited to available bandwidth, throughput, time delay, jitter and packet loss rate;
d2: constructing a corresponding hierarchical analysis judgment matrix A ═ (a) according to different service typesij)l×lWherein a isijRepresenting the importance degree of the network attribute to the service type, and assigning according to a 1-9 scale rule;
d3: calculating weight value lambda of each network attribute by adopting feature root methodmaxObtaining a corresponding characteristic vector omega; wherein, each element in the feature vector omega is a weight value of each network attribute;
d4: and (4) carrying out consistency check on the weighted values, calculating a consistency index, and if the consistency ratio is less than or equal to 0.1, analyzing and judging the consistency of the matrix by levels to meet the requirement.
Still further, in step S402, the following is specifically performed:
q1: according to available wireless network list
Figure BDA0002779977090000041
Obtaining actual attribute data of each wireless network, wherein the number of network attributes is m;
q2: normalizing the wireless network attribute data, wherein each normalized parameter value is xij；
Q3: determining entropy values of various types of reference attributes, wherein the formula is as follows:
Figure BDA0002779977090000042
Figure BDA0002779977090000051
wherein, gijThe specific weight of the jth parameter in the network i in all the alternative networks is calculated; e.g. of the typejEntropy value of j network performance parameter index; n is the number of available networks; m is the number of network attributes; k is a constant value, and k ═ 1/ln (n);
q4: calculating weight s of each reference attribute by using entropyjThe formula is as follows:
Figure BDA0002779977090000052
Figure BDA0002779977090000053
wherein p isjIs the difference coefficient of the j parameter, and
Figure BDA0002779977090000054
further, in step S403, a comprehensive weight is calculated by using the subjective weight matrix and the objective weight, and the specific formula is as follows:
Wj＝α·ω+(1-α)·sj,
wherein, WjFor the composite weight, α is the weighting factor.
Still further, in step S404, the specific formula is as follows:
Figure BDA0002779977090000055
Figure BDA0002779977090000056
Figure BDA0002779977090000057
wherein, FiIs the utility value of the ith network, FmaxFor the maximum utility value among all alternative networks, FcurFor the utility value of the current access network, FbestThe utility value of the access network is finally selected.
Still further, in step S5, the specific steps are as follows:
s501: after selecting to access the wireless network, repeating the steps 1 to 2, namely collecting attribute data of the current connected network and the nearby available wireless network;
s502: calculating utility values of the current wireless network and the standby wireless network according to S3-S4;
s503: and sequencing the utility values, if the utility value of the current wireless network is in the front of the utility values of all the standby wireless networks in a continuous period of time, maintaining the current network connection state, and otherwise, repeating S1-S5.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
1. the present invention takes into account both the situation of the mobile terminal and the situation of the current access to the wireless network. Firstly, in terms of a mobile terminal, the moving speed of the mobile terminal is a factor affecting a network scanning period, which is specifically shown in that when the moving speed of the terminal is higher, the network scanning period should be smaller, so as to prevent the terminal from being unable to discover an available new network in time, which causes network discovery delay and reduces handover efficiency. Secondly, in the network aspect, because the received signal power represents the energy of the network providing the basic communication service, the received signal power of the current access network received by the mobile terminal is adopted as an index for measuring the current access network condition. Specifically, the smaller the signal strength of the current access network is, the worse the current access network condition is, the stronger the urgency of the terminal to switch the network is, so it is necessary to speed up the network scanning and accordingly reduce the network scanning period.
Drawings
Fig. 1 is a schematic diagram of a prior art handover process.
Fig. 2 is a flow chart of the method according to the present embodiment.
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 are used for illustration only, and should not be construed as limiting the patent. 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.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
As shown in fig. 2, a method for cross-domain convergence handover of a heterogeneous network includes the following steps:
step S1: the method comprises the following steps that a mobile terminal accessed to a heterogeneous network carries out self-adaptive scanning on a current accessed wireless network and surrounding wireless networks and uploads collected data to a wireless access point;
step S2: each wireless access point in the control range of the centralized hub node periodically measures network attribute data in the range and uploads the network attribute data to the centralized hub node;
step S3: the centralized hub node performs service perception according to data uploaded by the wireless access point and performs switching prejudgment;
step S4: the centralized hub node performs service quality perception according to the network attribute data in the available network list, and selects the optimal network from the rest networks for switching;
step S5: the centralized hub node periodically measures the network attribute data of the currently connected network, and if the performance meets the requirement, the network attribute data is maintained unchanged, otherwise, the operation returns to the step S1 for execution.
In a specific embodiment, the mobile terminal in this embodiment is specifically a multimode terminal with multiple wireless interfaces, where the wireless interfaces include but are not limited to GSM, LTE, WLAN, wireless ad hoc networks, and the like, and the mobile terminal includes a first data collection module, a first data processing module, a first timing scanning module, and a first communication module.
In a specific embodiment, the specific steps of step S1 are as follows:
s101: a first data collection module of the mobile terminal collects link characteristics and service attributes of the mobile terminal in a currently connected wireless network, and the strength and the moving speed of a signal received by the mobile terminal;
s102: the mobile terminal performs first preprocessing on the collected data by using a first data processing module, wherein the first preprocessing includes but is not limited to removing abnormal values in original data and filling missing values, so that data cleaning is realized; according to the time-space characteristics and the change rule of the data, the data can be generally cleaned by methods such as probability statistics, neighbor analysis, classification and identification and the like;
the data cleansing is as follows:
1. methods used to identify anomalous data include, but are not limited to, descriptive statistics, three sigma, boxplots, and the like. The description will be given by taking the three-sigma method as an example. Wherein, the three-sigma method means that when the data obeys normal distribution, 99% of the numerical values should be within a distance of 3 standard deviations from the mean value, namely P (| x- μ | >3 σ) ≦ 0.003, and when the numerical values exceed the distance, the data is judged to be error data;
2. methods used to fill in missing values include, but are not limited to, mean filling, cluster filling, and multiple interpolation. The mean-filling method is described as an example. And filling a numerical null value as an average value of values of all other objects, and filling a non-numerical null value as a value with the highest occurrence frequency in all other objects.
S103: the first timing scanning module of the mobile terminal adaptively sets a scanning period according to the first preprocessed data; the specific set scanning period is as follows:
a1: the mobile terminal sets the maximum and minimum network scanning periods as TmaxAnd TminSimultaneously setting the signal strength threshold value of the terminal access network as RSSthThe maximum moving speed of the mobile terminal is Vmax；
A2: the mobile terminal RSS according to the current access network signal intensitycurAnd the current moving speed V of the terminalcurThe current dynamic scan period is calculated as follows:
Figure BDA0002779977090000071
a3: if the current scanning time period is less than the minimum time period, the current scanning period value is set as the minimum time period, and if the current scanning time period is greater than the maximum time period, the current scanning period value is set as the maximum time period.
S104: the first data collection module of the mobile terminal scans the currently connected wireless network and the surrounding wireless networks according to a set scanning period;
s105: step 102 and step 104 are repeated, and the scanned available network set is N ═ N-1，N2，...，NlAnd l represents the number of available wireless networks scanned by the mobile terminal.
In a specific embodiment, the wireless access point refers to a device which has general computing capability and storage capability, can run a simple algorithm model, and can store all data uploaded by each mobile terminal connected with the wireless access point, and the wireless access point comprises a second data collection module, a second data processing module and a second communication module;
in a specific embodiment, step S2 includes the following steps:
s201: the second data collection module of each wireless access point collects network attribute data in the coverage range of each wireless access point through devices such as a counter and a sensor, wherein the network attribute data comprises but is not limited to available bandwidth, throughput, time delay, jitter and packet loss rate;
s202: the second data processing module of each wireless access point performs second preprocessing on the collected network attribute data, wherein the second preprocessing includes but is not limited to removing abnormal values and filling missing values in the network attribute data, so that data cleaning is realized; the data cleansing is as follows:
1. methods used to identify anomalous data include, but are not limited to, descriptive statistics, three sigma, boxplots, and the like. The description will be given by taking the three-sigma method as an example. Wherein, the three-sigma method means that when the data obeys normal distribution, 99% of the numerical values should be within a distance of 3 standard deviations from the mean value, namely P (| x- μ | >3 σ) ≦ 0.003, and when the numerical values exceed the distance, the data is judged to be error data;
2. methods used to fill in missing values include, but are not limited to, mean filling, cluster filling, and multiple interpolation. The mean-filling method is described as an example. And filling a numerical null value as an average value of values of all other objects, and filling a non-numerical null value as a value with the highest occurrence frequency in all other objects.
S203: the second data processing module processes the second preprocessed data, counts the data according to a corresponding attribute index calculation formula, and uploads the data together with other attribute data; the network involved in the embodiment includes not only a mature LTE network but also a short-wave and ultra-short-wave network. Short-wave and ultrashort-wave networks do not have the mature gateway statistical function in LTE, so the collected data may be of a counter type, for example, packet loss rate data is determined by the number of transmitted packets and the number of received packets collected every fifteen minutes, which is determined by simple calculation, and is not a directly collected value, and so on, other data also needs a corresponding attribute index calculation formula for calculation.
S204: and the second communication module of each wireless access point uploads the processed network attribute data and the data collected by the mobile equipment connected with the network attribute data to the centralized hub node.
In a specific embodiment, the centralized hub node refers to a device that has strong computing capability and storage capability, can run a complex algorithm model, can store all data uploaded by each wireless access point connected with the device, is connected with the wireless access points through interfaces, supports interaction of control and service information, realizes switching management and the like, and comprises a storage module, a service sensing module, a network pre-decision module, a network selection module, a network detection module and a third communication module;
in a specific embodiment, step S3 includes the following steps:
s301: a service perception module of the centralized hub node establishes a service perception information base according to the service type and corresponding service data formulated by the 3 GPP; the service types comprise a session type, a streaming media type, an interaction type and a background type; the service perception information base comprises different specific port numbers corresponding to different service types; the data needs to provide a numerical range of the corresponding high-priority attribute, for example, in the streaming media service, a value range of the attributes such as bandwidth and throughput needs to be provided.
S302: a service sensing module of the centralized hub node senses the service type of the mobile terminal by using the uploaded specific port number, and finds the service type and service data corresponding to the port number in a service sensing information base;
s303: network pre-decision module utilization of centralized hub nodeThe perceived service type and the corresponding service data are compared with the network attribute data in the available network set N; the specific compared attributes include, but are not limited to, available bandwidth, throughput, delay, jitter, packet loss rate, and the like. If all the network attribute data meet the data requirements in the service perception information base, the wireless network is continuously reserved in the available network set; if one or more of the available networks are not accordant, the wireless network number is deleted from the available network set, and the rest available network set is represented as
Figure BDA0002779977090000091
Where n represents the number of available wireless networks.
In a specific embodiment, step S4 includes the following steps:
401: the network selection module determines a subjective weight matrix of the reference network attribute under different service types according to different service types formulated in 3 GPP;
this example is illustrated by an analytic hierarchy process:
step S401, specifically:
d1: determining reference attributes selected by a network, wherein the reference attributes include but are not limited to available bandwidth, throughput, time delay, jitter, packet loss rate and the like;
d2: constructing a corresponding hierarchical analysis judgment matrix A ═ (a) according to different service typesij)l×lWherein a isijRepresenting the importance degree of the network attribute to the service type, and assigning according to a 1-9 scale rule;
d3: calculating weight value lambda of each network attribute by adopting feature root methodmaxObtaining a corresponding characteristic vector omega; wherein, each element in the feature vector omega is a weight value of each network attribute;
d4: and (4) carrying out consistency check on the weighted values, calculating a consistency index, and if the consistency ratio is less than or equal to 0.1, analyzing and judging the consistency of the matrix by levels to meet the requirement.
S402: determining an objective weight matrix by using actual network attribute data uploaded by each wireless access point; the entropy weight method is described as follows:
q1: according to available wireless network list
Figure BDA0002779977090000101
Obtaining actual attribute data of each wireless network, wherein the number of network attributes is m;
q2: normalizing the wireless network attribute data, wherein each normalized parameter value is xij；
Q3: determining entropy values of various types of reference attributes, wherein the formula is as follows:
Figure BDA0002779977090000102
Figure BDA0002779977090000103
wherein, gijThe specific weight of the jth parameter in the network i in all the alternative networks is calculated; e.g. of the typejEntropy value of j network performance parameter index; n is the number of available networks; m is the number of network attributes; k is a constant value, and k ═ 1/ln (n);
q4: calculating weight s of each reference attribute by using entropyjThe formula is as follows:
Figure BDA0002779977090000104
Figure BDA0002779977090000105
wherein p isjIs the difference coefficient of the j parameter, and
Figure BDA0002779977090000106
s403: calculating a comprehensive weight value by utilizing a subjective weight value matrix and an objective weight value matrix through a set weighting factor, wherein a specific formula is as follows:
Wj＝α·ω+(1-α)·sj,
wherein, WjFor the composite weight, α is the weighting factor.
S404: and the network selection module obtains the utility value of each wireless network by using a simple weighting method according to the comprehensive weight value obtained in the step S403, if the maximum utility value in the alternative wireless network is equal to the utility value of the currently accessed wireless network or the ratio of the maximum utility value to the utility value is smaller than a set threshold value, the mobile terminal stays in the currently accessed wireless network, and otherwise, the wireless network with the maximum utility value is selected as the access network for switching.
In a specific embodiment, in step S404, the specific formula is as follows:
Figure BDA0002779977090000111
Figure BDA0002779977090000112
Figure BDA0002779977090000113
wherein, FiIs the utility value of the ith network, FmaxFor the maximum utility value among all alternative networks, FcurFor the utility value of the current access network, FbestThe utility value of the access network is finally selected.
In a specific embodiment, in step S5, the centralized hub node periodically measures attribute data of the currently connected network and the nearby available wireless networks, and if the performance meets the predetermined requirement, the centralized hub node is maintained unchanged, otherwise, the steps S1 to S5 are repeated, and the specific steps are as follows:
s501: the network detection module of the centralized hub node utilizes the network data of each wireless access point uploaded by the storage module, and repeats the steps from S1 to S2 after selecting to access the wireless network, namely collecting the attribute data of the current connected network and the available wireless networks nearby;
s502: calculating utility values of the current wireless network and the standby wireless network according to S3-S4;
s503: and sequencing the utility values, if the utility value of the current wireless network is in the front of the utility values of all the standby wireless networks in a continuous period of time, maintaining the current network connection state, and otherwise, repeating S1-S5.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.

Claims (10)

1. A heterogeneous network cross-domain fusion switching method is characterized in that: the method comprises the following steps:
s1: performing self-adaptive scanning on a current access wireless network and surrounding wireless networks, and uploading collected data to a wireless access point;
s2: each wireless access point in the control range of the centralized hub node periodically measures network attribute data in the range and uploads the network attribute data to the centralized hub node;
s3: the centralized hub node performs service perception according to data uploaded by the wireless access point and performs switching prejudgment;
s4: the centralized hub node performs service quality perception according to the network attribute data in the available network list, and selects the optimal network from the rest networks for switching;
s5: the centralized hub node periodically measures the network attribute data of the currently connected network, and if the performance meets the requirement, the network attribute data is maintained unchanged, otherwise, the operation returns to the step S3 for execution.
2. The method for cross-domain converged handover of heterogeneous networks according to claim 1, wherein: the step S1 includes the following steps:
s101: collecting link characteristics and service attributes of the mobile terminal in a currently connected wireless network, and the signal strength and the moving speed received by the mobile terminal;
s102: performing first preprocessing on the collected data, wherein the first preprocessing comprises but is not limited to removing abnormal values in original data and filling missing values, so as to realize data cleaning;
s103: adaptively setting a scanning period according to the data after the first preprocessing;
s104: scanning a currently connected wireless network and surrounding wireless networks according to a set scanning period;
s105: step 102 and step 104 are repeated, and the scanned available network set is N ═ N-1，N2，...，NlAnd l represents the number of available wireless networks scanned by the mobile terminal.
3. The method for cross-domain converged handover of heterogeneous networks according to claim 2, wherein: step S2, the specific steps are as follows:
s201: each wireless access point collects network attribute data in the coverage range of each wireless access point, wherein the network attribute data comprises but is not limited to available bandwidth, throughput, time delay, jitter and packet loss rate;
s202: performing second preprocessing on the collected network attribute data, wherein the second preprocessing comprises but is not limited to removing abnormal values and filling missing values in the network attribute data, so that data cleaning is realized;
s203: processing the second preprocessed data, calculating according to a corresponding attribute index calculation formula, and uploading the data together with other network attribute data;
s204: and uploading the processed network attribute data and the data collected by the mobile equipment connected with the processed network attribute data to the centralized hub node.
4. The method for cross-domain converged handover of heterogeneous networks according to claim 3, wherein: step S3, the specific steps are as follows:
s301: the centralized hub node establishes a service perception information base according to the service type and corresponding service data formulated by the 3 GPP; the service types comprise a session type, a streaming media type, an interaction type and a background type; the service perception information base comprises different specific port numbers corresponding to different service types;
s302: sensing the service type of the mobile terminal by using the uploaded specific port number, and finding the service type and service data corresponding to the port number in a service sensing information base;
s303: comparing the perceived service type and the corresponding service data with the network attribute data in the available network set N; if all the network attribute data meet the data requirements in the service perception information base, the wireless network is continuously reserved in the available network set; if one or more of the available networks are not accordant, the wireless network number is deleted from the available network set, and the rest available network set is represented as
Figure FDA0002779977080000021
Figure FDA0002779977080000022
Where n represents the number of available wireless networks.
5. The method for cross-domain converged handover of heterogeneous networks according to claim 4, wherein: step S4, the specific steps are as follows:
401: determining a subjective weight matrix of a reference network attribute under different service types according to different service types formulated in 3 GPP;
s402: determining an objective weight matrix by using actual network attribute data uploaded by each wireless access point;
s403: calculating a comprehensive weight value by using a subjective weight value matrix and an objective weight value matrix through a set weighting factor;
s404: and (4) obtaining the utility value of each wireless network by using a weighting method according to the comprehensive weight value obtained in the step (S403), if the maximum utility value in the alternative wireless network is equal to the utility value of the current access wireless network or the ratio of the maximum utility value to the utility value is less than a set threshold value, the mobile terminal stays in the current access wireless network, and otherwise, the wireless network with the maximum utility value is selected as the access network for switching.
6. The method for cross-domain converged handover of the heterogeneous network according to claim 5, wherein: in step S401, the step of, specifically,
d1: determining reference attributes selected by a network, wherein the reference attributes include but are not limited to available bandwidth, throughput, time delay, jitter and packet loss rate;
d2: according to different service types, constructing a hierarchical analysis judgment matrix A of each service as (a)ij)l×lWherein a isijRepresenting the importance degree of the network attribute to the service type, and assigning according to a 1-9 scale rule;
d3: calculating weight value lambda of each network attribute by adopting feature root methodmaxObtaining a corresponding characteristic vector omega; wherein, each element in the feature vector omega is a weight value of each network attribute;
d4: and (4) carrying out consistency check on the weighted values, calculating a consistency index, and if the consistency ratio is less than or equal to 0.1, analyzing and judging the consistency of the matrix by levels to meet the requirement.
7. The method for cross-domain converged handover of the heterogeneous network according to claim 6, wherein: step S402, specifically, as follows:
q1: according to available wireless network list
Figure FDA0002779977080000031
Obtaining actual attribute data of each wireless network, wherein the number of network attributes is m;
q2: normalizing the wireless network attribute data, wherein each normalized parameter value is xij；
Q3: determining entropy values of various types of reference attributes, wherein the formula is as follows:
Figure FDA0002779977080000032
Figure FDA0002779977080000033
wherein, gijThe specific weight of the jth parameter in the network i in all the alternative networks is calculated; e.g. of the typejEntropy value of j network performance parameter index; n is the number of available networks; m is the number of network attributes; k is a constant value, and k ═ 1/ln (n);
q4: calculating weight s of each reference attribute by using entropyjThe formula is as follows:
Figure FDA0002779977080000034
Figure FDA0002779977080000035
wherein p isjIs the difference coefficient of the j parameter, and
Figure FDA0002779977080000036
8. the method for cross-domain converged handover of heterogeneous networks according to claim 7, wherein: in step S403, a comprehensive weight is calculated by using the subjective weight matrix and the objective weight, and the specific formula is as follows:
Wj＝α·ω+(1-α)·sj,
wherein, WjFor the composite weight, α is the weighting factor.
9. The method for cross-domain converged handover of heterogeneous networks according to claim 8, wherein: in step S404, the specific formula is as follows:
Figure FDA0002779977080000041
Figure FDA0002779977080000042
Figure FDA0002779977080000043
wherein, FiIs the utility value of the ith network, FmaxFor the maximum utility value among all alternative networks, FcurFor the utility value of the current access network, FbestThe utility value of the access network is finally selected.
10. The method for cross-domain converged handover of heterogeneous networks according to claim 9, wherein: step S5, the specific steps are as follows:
s501: after selecting to access the wireless network, repeating the steps 1 to 2, namely collecting attribute data of the current connected network and the nearby available wireless network;
s502: calculating utility values of the current wireless network and the standby wireless network according to S3-S4;
s503: and sequencing the utility values, if the utility value of the current wireless network is in the front of the utility values of all the standby wireless networks in a continuous period of time, maintaining the current network connection state, and otherwise, repeating S3-S5.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101404660A (en) * 2008-11-17 2009-04-08 中国科学院计算技术研究所 Service flow distribution system and method for multi-module cooperation communication
US20100150111A1 (en) * 2008-12-08 2010-06-17 Xg Technology, Inc. System and method for adaptive proactive scanning to support fast handoffs in mobile networks
CN109548102A (en) * 2019-01-08 2019-03-29 重庆邮电大学 A kind of network vertical handoff method based on the cognitive radio adaptive scanning period

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101404660A (en) * 2008-11-17 2009-04-08 中国科学院计算技术研究所 Service flow distribution system and method for multi-module cooperation communication
US20100150111A1 (en) * 2008-12-08 2010-06-17 Xg Technology, Inc. System and method for adaptive proactive scanning to support fast handoffs in mobile networks
CN109548102A (en) * 2019-01-08 2019-03-29 重庆邮电大学 A kind of network vertical handoff method based on the cognitive radio adaptive scanning period

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
李洋;张静;: "一种基于周期自适应的垂直切换算法" *
陶洋;纪瑞娟;杨理;王进;: "基于动态扫描周期的多属性垂直切换算法" *

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