Edge Computing Tasks Orchestration: An Energy-Aware Approach

Abstract

In this paper, we investigate experimentally the use of auctioning as a method for optimizing task orchestration in distributed computing systems by making selfish agents compete to execute computational tasks. Our goal is to find an approach that can improve the performance of these systems, using a deadline, fines, and reward limits in a reverse second-price sealed bid auction, to incentive and control the system, specifically in terms of improving task throughput and power consumption. With improvements to both energy consumption and task throughput, we have developed a promising approach, that is able to scale with the number of machines in the system. Results suggest that this type of auction may be useful for improving the implementation of these systems in a wide range of scenarios.