Research On Multi Objective Task Offloading Strategy Based On BBO In Mobile Edge Computing

With the widespread use of mobile devices,applications such as face recognition,data stream processing,and interactive gaming are being used on a large scale.These types of applications usually require intensive computing resources and high energy consumption.However,due to physical resource limitations,mobile devices generally have only limited computing power and battery life.Mobile Edge Computing(MEC)system can provide efficient computing enhancement services for mobile devices.Among them,the task offloading problem will directly affect the energy consumption,cost and task completion time of the entire MEC system.Therefore,the task offloading problem is a worthy research problem in mobile edge computing.Biogeography-Based Optimization(BBO)is an algorithm to solve problems by simulating the distribution of organisms in geography.This algorithm has a good advantage in dealing with multi-objective optimization problems.Taking advantage of the advantages of BBO in dealing with multi-objective optimization problems,this thesis optimizes the energy consumption,time and cost of MEC task offloading based on BBO algorithm.The main contributions of this thesis are as follows:1.Aiming at the problem of unbalanced consideration of multiple targets when offloading MEC tasks in the current research,this thesis proposes a task offloading strategy based on the BBO algorithm.By introducing BBO algorithm,this strategy fully considers the optimization problems of time,energy consumption and other objectives.And the experiments are conducted by using i Fog Sim platform.The experimental results show that the offloading strategy proposed in this thesis has significant optimization effect in terms of time,slightly improved in terms of energy consumption,and also has a good performance in terms of cost.It is a good choice to use this strategy to solve the multi-objective task offloading problem when the mobility requirements are weak.2.Aiming at the problem that mobility is not sufficiently considered in the current research on task offloading,this thesis proposes an adaptive task unloading strategy based on the BBO algorithm on the basis of the above research.By adding an adaptive module to the offloading strategy of the BBO algorithm,the offloading destinations can be filtered so that the task completion time demanded by higher mobility can be met.And the experiments are conducted by using i Fog Sim platform.Experimental results show that under higher mobility requirements,this strategy can be further improved on the basis of the above-mentioned research.The optimization of energy consumption has increased by3%,and the optimization of cost can be up to 37%.In the case of strong mobility requirements,using this strategy to solve the problem of multi-target task offloading will be a good choice.