Energy-Aware Scheduling of Real-Time Tasks in Wireless Networked Embedded Systems

Recent technological advances have opened up several distributed real-time applications involving battery-driven embedded devices with local processing and wireless communication capabilities. Energy management is the key issue in the design and operation of such systems. In this paper, we consider a single-hop networked real-time embedded system where each node supports both dynamic voltage scaling (DVS) and dynamic modulation scaling (DMS) power management techniques to tradeoff time for energy savings. In this model, we address the problem of scheduling periodic complex tasks where each task consists of several precedence constrained message passing sub-tasks. Our contributions towards this problem are twofold. First, we analyze the system level energy-time tradeoffs considering both the computation and communication workloads by defining a novel energy gain metric. We then present static (centralized) and dynamic (distributed) energy gain based slack allocation algorithms which reduce the total energy consumption, while guaranteeing the ready time, deadline and precedence constraints. We compare the performance of the proposed algorithms with several baseline algorithms through simulation studies. Our results show that the proposed algorithms perform significantly better than the baseline algorithms for the simulated conditions. Finally, we identify several interesting energy-aware research problems in the area of networked real-time embedded systems.