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Mobile edge computing (MEC) provides users with a high quality experience(QoE) by placing servers with rich services close to the end users. Comparedwith local computing, MEC can contribute to energy saving, but results inincreased communication latency. In this paper, we jointly optimize taskoffloading and resource allocation to minimize the energy consumption in anorthogonal frequency division multiple access (OFDMA)-based MEC networks, wherethe time-sensitive tasks can be processed at both local users and MEC servervia partial offloading. Since the optimization variables of the problem arestrongly coupled, we first decompose the original problem into two subproblemsnamed as offloading selection (PO), and subcarriers and computing resourceallocation (PS), and then propose an iterative algorithm to deal with them in asequence. To be specific, we derive the closed-form solution for PO, and dealwith PS by an alternating way in the dual domain due to its NP-hardness.Simulation results demonstrate

Energy Minimization for Mobile Edge Computing Networks with Time-Sensitive Constraints