A Cooperative Computation Offloading Scheme for Dense Wireless Sensor-assisted Smart Grid Networks
Jin Jiang, Jian Fei Xu, Yao Xie, Yiwei Zhu, Zhongbin Li, Chen Yang · 2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) · 2021
The emerging applications in wireless sensor-based smart grid networks has provided higher demands on latency, and such latency-sensitive applications also require dense computations, especially in dense wireless sensor networks. To further satisfy the huge demands on communication and computation resources, mobile edge computing (MEC) has been proposed to offload computation tasks from terminals to nearby MEC servers that are deployed on wireless sensors. However, in the practical scenario, due to the expensive cost of deploying MEC servers, the amount of the deployed MEC servers is always limited, i.e., it may be much lower than that of sensors or terminals. As a result, the computation offloading in MEC-assisted dense wireless sensor network still faces open challenges. To address the above issue, we propose a joint MEC and device-to-device(D2D)-based computation offloading scheme. Specifically, we formulate the computation offloading problem as a joint access selection and resource allocation optimization, which minimizes the energy consumption while requested bandwidths and delay are satisfied. Then, we solve the formulated problem by designing a quantum behaved particle swarm optimization (QPSO) algorithm. The simulation results demonstrate that the proposed scheme can improve the efficiency of computation offloading and decrease the energy consumption in the MEC-assisted dense wireless sensor-based smart grid networks.