Earliest Deadline First Scheduling for Real-Time Computing in Sustainable Sensors

Abstract

Energy harvesting is a green technology that authorizes small electronic devices to be supplied for perpetual operation. It enables wireless sensors to be integrated in applications that previously were not feasible with conventional battery-powered designs. Intermittent computing and scheduling are the two central aspects of designing a Real-Time Energy Harvesting (RTEH) sensor, generally used to monitor a mission critical process. Traditional scheduling algorithms fail to timely execute the hard deadline tasks because they accommodate no fluctuations in power supply and therefore no intermittent computing. A suitable energy-harvesting-aware scheduling algorithm has been proposed so as to achieve a higher schedulability rate. Unlike the classical EDF (Earliest Deadline First) scheduler, the ED-H algorithm is idling and clairvoyant, with an improved performance in terms of the deadline missing ratio. This paper reviews the main advances in dynamic priority scheduling based on EDF for energy-neutral systems.

Traffic Classification and Packet Scheduling Strategy with Deadline Constraints for Input-Queued Switches in Time-Sensitive Networking

“…Unfortunately, the limitation of the von Neumann matrix decomposition algorithm is that it is only applicable to solving single-class packet scheduling problems and cannot effectively solve two-class or multi-class scheduling problems. Traditional methods for solving the multi-class scheduling problem involve using algorithms such as Earliest Deadline First (EDF) or Minimum Laxity First (MLF) and their variants as detailed in [23][24][25][26]. Traditional heuristic algorithms have the advantage of low complexity, but they also have room for improvement in QoS performance metrics, such as throughput, packet loss, and delay.…”