Energy-delay-cost Tradeoff for Task Offloading in Imbalanced Edge Cloud Based Computing
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In this paper, the imbalance edge cloud based computing offloading for multiple mobile users (MUs) with multiple tasks per MU is studied. In which, several edge cloud servers (ECSs) are shared and accessed by multiple wireless access points (APs) with the backhaul links, and each MU has multiple computing intensive and latency critical tasks should be offloaded to execute, which involves both the AP association and ECS selection, with the objective of minimizing the offloading cost. Distinguished with existing research, besides the transmission delay and energy consumption from MU to AP, the ECS access-cost which characterizes the ECS access delay and (or) resource using cost is introduced, thus finally formulates the delay-energy-cost tradeoff based offloading cost criteria, for the MUs' offloading decision and resource allocation problems. In specific, in our system, the ECS access-cost depends on both the AP and ECS, which reflects the effects of different backhaul techniques used by these APs, and their negotiated payments of ECS resource using under different service level agreements. Both problems of minimizing the sum offloading costs for all MUs (efficiency-based) and minimizing the maximal offloading cost per MU (fairness-based) are discussed. Since these problems are all NP-hard. Therefore, some centralized and distributed heuristic algorithms are proposed to find the suboptimal solutions. Further analysis and numerical results are presented at last to demonstrate the performance of these algorithms from several aspects, such as efficiency, complexity and fairness.
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