ENERGY EFFICIENT SCHEDULING FOR REAL-TIME EMBEDDED SYSTEMS WITH PRECEDENCE AND RESOURCE CONSTRAINTS

Energy consumption is a critical design issue in real-time systems, especially in battery- operated systems. Maintaining high performance, while extending the battery life between charges is an interesting challenge for system designers. Dynamic Voltage Scaling and Dynamic Frequency Scaling allow us to adjust supply voltage and processor frequency to adapt to the workload demand for better energy management. Usually, higher processor voltage and frequency leads to higher system throughput while energy reduction can be obtained using lower voltage and frequency. Many real-time scheduling algorithms have been developed recently to reduce energy consumption in the portable devices that use voltage scalable processors. For a real-time application, comprising a set of real-time tasks with precedence and resource constraints executing on a distributed system, we propose a dynamic energy efficient scheduling algorithm with weighted First Come First Served (WFCFS) scheme. This also considers the run-time behaviour of tasks, to further explore the idle periods of processors for energy saving. Our algorithm is compared with the existing Modified Feedback Control Scheduling (MFCS), First Come First Served (FCFS), and Weighted scheduling (WS) algorithms that uses Service-Rate-Proportionate (SRP) Slack Distribution Technique. Our proposed algorithm achieves about 5 to 6 percent more energy savings and increased reliability over the existing ones