Research On Mobility Management Scheme Based On Game Theory In Internet Of Things Scenarios

In recent years,with the intensive deployment of heterogeneous networks(Het Net)and the development of Internet of Things(Io T)technology,the number and performance of mobile terminals and access points have achieved leapfrog growth.At the same time,it has also promoted the gradual realization of global coverage and seamless switching wireless communication goals,to some extent meeting the growing traffic demand in people’s daily lives.Faced with the increasing density of base stations,mobility management in networks has become a research hotspot under emerging network architectures.However,the sharp increase in the number of micro base stations has not alleviated the load pressure on macro base stations.Therefore,long-term access strategies and optimization schemes for mobile correlation during the mobile terminal movement process have become important research topics affecting mobility management solutions in Het Net.To study the above content,it is necessary to address the challenges faced by the mobility management of large-scale mobile terminals in Het Net.On the one hand,there are many problems of network congestion and poor terminal experience caused by blind wireless access choices of mobile terminals.How to optimize the decisionmaking of mobile terminals in wireless access to improve the overall effectiveness of the network;On the other hand,there is an imbalance in the load of each base station and a long interruption time for mobile terminals.How to develop an effective terminal base station association scheme to improve load balancing and handover efficiency.Since the game theory method can ensure that all participants achieve their goals in the process of mutual restriction and cooperation,and can be applied to the design of wireless access schemes for mass terminals in Het Net.Therefore,this thesis focuses on the above challenges and adopts game theory to study mobility management in the Internet of Things.The main work is as follows:1)In order to solve the problem of low network utility caused by improper wireless access selection of terminals in Het Net,a reinforcement learning selection scheme based on "regret degree" is proposed based on the game theory model,which comprehensively considers the global network information of terminals and networks.The concept of regret degree is proposed to describe the difference of the gains obtained by terminals,and the probability of terminal access selection is optimized through the feedback of terminals to the global information of base stations;The regret degree of the terminal and base station is inputted into the semi Markov decision process and iterated to the optimal strategy through reinforcement learning.In addition,the effects of different parameters on system utility and switching performance were studied.The simulation results verify that this algorithm can reduce unnecessary switching and improve system throughput.2)To alleviate load imbalance and improve the efficiency of seamless handover in Het Net,an auction algorithm scheme based on Dual Active Protocol Stack(DAPS)is adopted to transform the wireless access selection of terminals into a terminal base station association process in the mobile process.Firstly,a terminal base station association graph is constructed before the mobile handover occurs,and an auction algorithm is used to solve for the maximum weighted matching of the graph,optimizing the number of terminals that the base station can connect to.Secondly,during the handover process,a DAPS based solution is adopted to accelerate the speed of wireless link interruption and reconnection,effectively avoiding the problem of long mobile interruption time caused by handover interruption.Finally,through comparative experiments,it was found that the auction algorithm scheme based on DAPS can significantly improve load balancing and reduce switching latency compared to other algorithms.