Research On Key Technologies Of Service Migration To Wireless Metropolitan Area Network In Edge Computing Environment

Nowadays,with the development of wireless communication,people rely more and more heavily on mobile devices due to the diversification of application deployment and personalized service requirements in wireless metropolitan area network(WMAN).With the rapid rise of edge computing,the services in WMAN are migrated to the edge nodes(ENs)for execution by mobile users,which reduces the service execution time and the energy consumption of mobile devices.However,due to the large volume of services and limited resources of ENs in WMAN,problems such as poor service transmission performance and increased energy consumption of ENs have become increasingly prominent.In the era of big data where privacy data is so important,how to ensure privacy during service migration and realize privacy-aware service migration is urgent.Therefore,the service migration for WMAN in edge computing faces the following challenges: 1)In view of the placement strategy for batch edge services,the characteristics of large service volume and multiple sources are ignored,and the trade-off between server performance and energy consumption is lack;2)In view of the privacy leakage during service migration,it is necessary to comprehensively consider the complexity of privacy protection during the service migration between ENs while ensuring the execution efficiency.To cope with the above challenges,this paper researches on the key technologies of service migration for MWAN in edge computing.The main work mainly includes:(1)To comprehensively consider resource utilization and energy consumption of ENs,a service placement method is proposed to optimize the network performance and energy consumption.Specifically,firstly,establish the resource utilization model,energy consumption model and service execution time model.Then,leveraging Strength Pareto Evolutionary Algorithm(SPEA),a balanced set of service placement strategies is obtained.Finally,leveraging Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)and the Multiple Criteria Decision Making(MCDM),the final service placement strategy is acquired.The joint optimization of resource utilization and energy consumption is realized under the requirement of service execution time.(2)In response to the lack of privacy protection during service migration,a privacy-aware service migration method is proposed.Specifically,firstly,establish the load balance model,service migration time model and privacy entropy model.Then,leveraging Improving the Strength Pareto Evolutionary Algorithm(SPEA2),a balanced set of service migration strategies is acquired.Finally,evaluate the utility value of each migration strategy and select the strategy with the best utility value as the final service migration strategy to realize the joint optimization of network load balance,service migration time and privacy entropy.