Edge-side task scheduling: Auction mechanism and genetic algorithm based methods

Abstract

Edge computing is an emerging computing architecture. The scheduling and optimization of the tasks on the edge side of the smart factory can effectively reduce the processing delay and improve the utilization efficiency of servers. This study focuses on the problem of edge-side task scheduling with the goal of minimizing the maximum completion time of the tasks. A first-price sealed-bid auction based algorithm and a genetic algorithm with elite retention strategy are designed to solve the problem. The experimental results indicate that the auction-based scheduling algorithm has better real-time performances compared to the genetic algorithm.