Joint Demand Response and Task Offloading Strategy for 5G Edge Computing Network

doi:10.11930/j.issn.1004-9649.202112071

Abstract

Abstract: Along with the dramatic increase in demand for IoT communication computing, the 5G communication and edge computing network gradually become the emerging high energy consumption load. In response to the high electricity bill of 5G edge computing network, this paper proposes a joint task offloading and demand response strategy for 5G edge computing network. By jointly adjusting the allocation of communication and computing resources, the task offloading decision and the charging/discharging of 5G base station battery, the proposed strategy can reduce the electric bill by transferring the task loads or sacrificing the delay performance, and provide considerable response capacity to power grid. To solve the Mixed Integer Non-linear Programming (MINLP) problem, this paper further proposes a Generalized Benders Decomposition (GBD) algorithm based on network scenario division. By decomposing the problem into a master problem of task offloading decision and a primal problem of charging/discharging and resource allocation , the complexity of the model is reduced. The simulation results show that compared with the response strategy that only considers task offloading or communication resource allocation, the proposed strategy reduces the electric bill and avoid the deterioration of delay performance.

Key words: energy Internet, 5G, edge computing, task offloading, resource allocation, demand response

LU Xu, CHEN Ying, XU Zhongping, ZHANG Haiquan, MU Chunfang, CHEN Kai, SUN Yi. Joint Demand Response and Task Offloading Strategy for 5G Edge Computing Network[J]. Electric Power, 2022, 55(10): 209-218.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202112071

https://www.electricpower.com.cn/EN/Y2022/V55/I10/209

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