Joint optimization of Task Offloading and Computing Resource Allocation in MEC-D2D Network

Zhaoyuan Liu, Jingyi Fan, S. Geng, Peng Qin, Xiongwen Zhao
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Abstract

In mobile edge computing (MEC) network, computing offloading can alleviate resource constraints and improve service quality effectively. Meanwhile data transmission in Device-to-Device (D2D) communication can realize resource sharing and balance among different users, in order to improve system spectrum utilization and reduce communication delay. Aiming at minimizing the task delay and terminal energy consumption in MEC network, a joint optimization problem considering task offloading and computing resource allocation is formulated in D2D-assisted MEC network by building cost optimization model with multi-objective constraints. Moreover, the original problem is decoupled as two sub-problems which are solved by discrete ternary particle swarm optimization (DTPSO) algorithm and Lagrange multiplier method, respectively. Simulation results show that compared with three other typical methods, the proposed scheme in this work can effectively reduce task execution delay and terminal energy consumption.
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MEC-D2D网络中任务卸载与计算资源分配的联合优化
在移动边缘计算(MEC)网络中,计算卸载可以有效缓解资源约束,提高服务质量。同时,设备到设备(Device-to-Device, D2D)通信中的数据传输可以实现不同用户之间的资源共享和平衡,从而提高系统频谱利用率,降低通信延迟。以最小化MEC网络中的任务延迟和终端能耗为目标,通过建立多目标约束的成本优化模型,在d2d辅助MEC网络中构建了一个考虑任务卸载和计算资源分配的联合优化问题。将原问题解耦为两个子问题,分别用离散三元粒子群优化算法和拉格朗日乘子法求解。仿真结果表明,与其他三种典型方法相比,本文提出的方案能有效降低任务执行延迟和终端能耗。
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