Strategy for Task Offloading of Multi-user and Multi-server Based on Cost Optimization in Mobile Edge Computing Environment
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With the development of mobile edge computing, how to utilize the computing power of edge computing toeffectively and efficiently offload data and to compute offloading is of great research value. This paper studiesthe computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in orderto minimize system energy consumption, the problem is modeled by considering the joint optimization of theoffloading strategy and the wireless and computing resource allocation in a multi-user and multi-serverscenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. Asthe centralized optimization method is an NP problem, the game method is used to achieve effectivecomputation offloading in a distributed manner. The decision problem of distributed computation offloadingbetween the mobile equipment is modeled as a multi-user computation offloading game. There is a Nashequilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose adistributed computation offloading algorithm, which first calculates offloading weights, and then distributedlyiterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified bysimulation experiments. Simulation results show that our proposed algorithm can achieve the balance by alimited number of iterations. At the same time, the algorithm outperforms several other advanced computationoffloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.
Abstract
With the development of mobile edge computing, how to utilize the computing power of edge computing toeffectively and efficiently offload data and to compute offloading is of great research value. This paper studiesthe computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in orderto minimize system energy consumption, the problem is modeled by considering the joint optimization of theoffloading strategy and the wireless and computing resource allocation in a multi-user and multi-serverscenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. Asthe centralized optimization method is an NP problem, the game method is used to achieve effectivecomputation offloading in a distributed manner. The decision problem of distributed computation offloadingbetween the mobile equipment is modeled as a multi-user computation offloading game. There is a Nashequilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose adistributed computation offloading algorithm, which first calculates offloading weights, and then distributedlyiterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified bysimulation experiments. Simulation results show that our proposed algorithm can achieve the balance by alimited number of iterations. At the same time, the algorithm outperforms several other advanced computationoffloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.
참고문헌 (31)
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