Research On Performance Of Computation Offloading In Opportunity Network

Since the 21st century,the frequency of information communication has become higher and higher,and the Internet has enabled the world to exchange information on the same network platform.With the dramatic i ncrease in information communication,the demanding of mobile terminals has increased.With the development and innovation of technology,the te rminal equipment is getting smaller and smaller,and the APP application on the terminal is becoming more and more rich and complicated.Mobile payment,mobile medical,GPS positioning,and the popular VR technolo gy put high demands on the computing power,storage capacity and batte ry capacity of mobile terminals.Due to size,weight and heat dissipation,mobile terminals have a disadvantage in these respects compared to tradi tional fixed terminals.In this case,Computational migration,as an import ant part of mobile computing,is receiving more and more attention from researchers.For opportunistic network which makes network communicati on through node movement,this paper explores the target selection phase in the process of computing migration,analyzes the mobile migration-bas ed migration process,and explores the connection rate and energy consu mption of the node:(1)The connection rate is an important indicator affecting the comp utational migration performance in the opportunistic network,and it is als o an important reference for how to select the destination node.Through the secretarial problem in the optimal stopping theory,the relevant mathe matical model is established,and the target node with the optimal task c onnection rate is found,so as to achieve the performance optimization go al of calculating the migration process.(2)Since the mobile migration based on the opportunity network is performed between multiple mobile devices,the parameters,battery capaci ty,computing power,and storage capacity of the mobile device are often different in the actual environment,sometimes even The difference is ve ry large,then how to choose a service node with better performance and less energy consumption when the primary node or the source node deli vers the subtask is a problem to be solved.This strategy,under the assu mption that there is one source node and multiple service nodes,filters t he service nodes with optimal energy efficiency through the optimal stopp ing theory,and sends the subtasks to the node to save energy and impro ve efficiency.