Constraint-Aware Resource Management for Cyber-Physical Systems

Justin McGowen, Ismet Dagli, Neil T. Dantam, Mehmet E. Belviranli

Abstract: Cyber-physical systems (CPS) such as robots and self-driving cars pose strict physical requirements to avoid failure. Scheduling choices impact these requirements. This presents a challenge: how do we find efficient schedules for CPS with heterogeneous processing units, such that the schedules are resource-bounded to meet the physical requirements? We propose the creation of a structured system, the Constrained Autonomous Workload Scheduler, which determines scheduling decisions with direct relations to the environment. By using a representation language (AuWL), Timed Petri nets, and mixed-integer linear programming, our scheme offers novel capabilities to represent and schedule many types of CPS workloads, real world constraints, and optimization criteria.

External IDs:dblp:conf/date/McGowenDDB24