Dispatching Deadline Constrained Jobs in Edge Computing Systems

Abstract

The edge computing paradigm extends the architectural space of real-time systems by bringing the capabilities of the cloud to the edge. Unlike cloud-native systems designed for mean response times, real-time industrial embedded systems are designed to control a single physical system, such as a manipulator arm or a mobile robot, that requires temporal predictability. We consider the problem of dispatching and scheduling of jobs with deadlines that can be offloaded to the edge and propose DAL, a deadline-aware load balancing and scheduling framework that leverages the availability of on-demand computing resources along with an on-arrival dispatching scheme to manage temporal requirements of such offloaded applications. The evaluation indicates that DAL can achieve reasonably good performance even when execution times, arrival times, and deadlines vary.