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Joint Optimization of Computation Offloading and UL/DL Resource Allocation in MEC Systems

机译:MEC系统中的计算卸载和UL / DL资源分配的联合优化

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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.
机译:移动边缘计算(MEC)已成为第五代移动网络即将推出的时代的主导技术。通过将来自移动设备的任务卸载到由蜂窝基站提供的边缘云,可以减少能量消耗和移动任务的端到端延迟。在本文中,我们的目的是通过联合分配计算和通信资源来优化基于TDMA的MEC系统的延迟性能。我们的目标是最大限度地减少系统中所有设备的最大延迟。我们首先简化了优化问题并将其转换为凸起。然后,我们从最佳资源分配策略派生封闭式表达式,并调查上行链路和下行链路资源分配之间的关系。还开发了一个子梯度算法来解决联合资源分配问题。最后,验证了数值模拟结果,以验证我们的提案是否可以实现更好的性能与传统方案相比。

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