Affiliation:
1. Electric Power Science Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 211103, China
Abstract
In order to meet the edge services placement demand for multiobjective optimization of Power Internet of Things, an edge services placement strategy based on an improved strength Pareto evolutionary algorithm (SPEA2) is proposed in this paper. Firstly, we model the delay, resource utilization, and energy consumption. Then, a multiobjective optimization is proposed. Finally, an enhanced genetic algorithm is used to derive the decision candidate set. Moreover, the optimal solution in the candidate set is selected to be utilized in the iteration of the multicriteria decision and the superior-inferior solution distance method. Numerical results and analysis show that the proposed strategy is more effective in reducing system delay, improving resource utilization, and saving energy consumption than the other two benchmark algorithms.
Funder
Foundations of State Grid Corporation of China
Subject
Computer Networks and Communications,Information Systems