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Stochastic Resource Management for Mobile Edge Computing in 5G Networks

Mobile Edge Computing pushes the rich cloud resources to the edge of the network, solving some shortcomings of Cloud Computing. In the coming era of fifth generation (5G), mobile edge computing is a emergency platform to offer high experience to user. However, there are some limitation in mobile edge computing, i.e., the limitation of resources of edge servers. We consider a mobile edge computing system, consisting of smart mobile devices and edge servers. Each smart mobile device receives task and computes task at local, which its computation resource cannot completely compute task at one time slot. So each smart mobile device sends tasks to several edge servers. We formulate a stochastic problem to minimize the energy consumption and propose a Lyapunov-based framework to decompose the problem into two subproblems which determines the CPU-cycle frequency and the transmitted task in each time slots. Based on this, we developed a minimum energy consumption algorithm(ME) for mobile edge computing system. Extensive simulation results demonstrate the efficiency of our algorithm.