Scheduling Firm Real-time Applications on the Edge with Single-bit Execution Time Prediction

Abstract

The edge computing paradigm brings the capabilities of the cloud such as on-demand resource availability to the edge for applications with low-latency and real-time requirements. While cloud-native load balancing and scheduling algorithms strive to improve performance metrics like mean response times, real-time systems, that govern physical systems, must satisfy deadline requirements. This paper explores the potential of an edge computing architecture that utilizes the on-demand availability of computational resources to satisfy firm real-time requirements for applications with stochastic execution and inter-arrival times. As it might be difficult to know precise execution times of individual jobs prior to completion, we consider an admission policy that relies on single-bit execution time predictions for dispatching. We evaluate its performance in terms of the number of jobs that complete by their deadlines via simulations. The results indicate that the prediction-based admission policy can achieve reasonable performance for the considered settings.