Joint Optimization Of Computation Offloading And Ul/Dl Resource Allocation In Mec Systems

2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC)(2018)

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Abstract
Mobile edge computing (MEC) has become a dominant technology in the upcoming era of the 5th generation mobile networks. By offloading tasks from mobile devices to edge clouds provided by cellular base stations, both energy consumption and end-to-end delay of mobile tasks can be reduced. In this paper, we aim to optimize the latency performance of TDMA-based MEC systems by joint allocation of computation and communication resource. Our goal is to minimize the maximal delay of all devices in the system. We first simplify the optimization problem and convert it into a convex one. Then we derive the closed-form expression for the optimal resource allocation strategy and investigate the relationship between uplink and downlink resource allocation. A sub gradient algorithm is also developed to solve the joint resource allocation problem. Finally, numerical simulation results are shown to verify that our proposal can achieve a better performance compared with the traditional schemes.
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Key words
energy consumption,TDMA-based MEC systems,optimization problem,optimal resource allocation strategy,downlink resource allocation,joint resource allocation problem,joint optimization,5th generation mobile networks,uplink resource allocation,UL-DL resource allocation,edge clouds,subgradient algorithm,numerical simulation,cellular base stations,mobile edge computing,computation offloading
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