Service Scheduling Based on Edge Computing for Power Distribution IoT

  • Zhu Liu State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Xuesong Qiu State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Shuai Zhang State Grid Information & Telecommunication Group CO., LTD, Beijing 102211, China.
  • Siyang Deng State Grid Information & Telecommunication Group CO., LTD, Beijing 102211, China.
  • Guangyi Liu Global Energy Interconnection Research Institute North America, San Jose, CA,95134,USA.
Keywords: PD-IoT, edge computing, service scheduling, load balancing strategy, ant colony algorithm.

Abstract

With growing amounts of multi-micro grids, electric vehicles, smart home, smart cities are connected the Power Distribution Internet of Things (PD-IoT) system, massive grid data and business require greater computing resource and communication bandwidth for the distribution, and it probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence. This paper presents a service scheduling method based edge computing to balance the business load of PD-IoT. The architecture, components and functional requirements of the PD-IoT with edge computing platform are proposed. Then, the structure of the service scheduling system is presented. Further, a novel load balancing strategy and ant colony algorithm are investigated in the service scheduling method. The validity of the method is evaluated by simulation tests. Results indicate that the mean load balancing ratio is reduced by 99.16% and the optimized offloading links can be acquired within 1.8 iterations. Computing load of the nodes in edge computing platform can be effectively balanced through the service scheduling.

Published
2020-05-21
Section
Articles on Computers