Mobile-edge computing (MEC) has recently emerged as a promising paradigm toliberate mobile devices from increasingly intensive computation workloads, aswell as to improve the quality of computation experience. In this paper, weinvestigate the tradeoff between two critical but conflicting objectives inmulti-user MEC systems, namely, the power consumption of mobile devices and theexecution delay of computation tasks. A power consumption minimization problemwith task buffer stability constraints is formulated to investigate thetradeoff, and an online algorithm that decides the local execution andcomputation offloading policy is developed based on Lyapunov optimization.Specifically, at each time slot, the optimal frequencies of the local CPUs areobtained in closed forms, while the optimal transmit power and bandwidthallocation for computation offloading are determined with the Gauss-Seidelmethod. Performance analysis is conducted for the proposed algorithm, whichindicates that the power consumption and execution delay obeys an [O (1/V); O(V)] tradeoff with V as a control parameter. Simulation results are provided tovalidate the theoretical analysis and demonstrate the impacts of variousparameters to the system performance.
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