Improved Genetic Offloading Algorithm Based on Edge Terminal Server of Power Distribution Station Area

Abstract

Edge terminals will play a role in the smart distribution grid of the future, so it needs to process a large amount of user electricity consumption data, at the same time to meet the real-time requirements. The paper studies the multi-objective optimization task resource offloading algorithm for edge terminal server, such as computing power, service time, bandwidth, memory and so on. Firstly, the offloading model of edge computing resources for multi-objective optimization is proposed. On this basis, an improved genetic offloading algorithm is proposed to reduce the probability of population algorithm falling into local optimum by self-adaptation coefficient and factors of age and longevity. Meanwhile, the probability of finding the optimum solution is improved. Finally, the effectiveness of the proposed algorithm is verified through the Matlab/simulink simulation results.