Heuristic-Path and Observer based Low-Energy Scheduling Algorithms for Body Area Network Systems

In this paper, we propose novel low-energy static and dynamic scheduling algorithms for the heterogeneous Body Area Network (BAN) systems, where task graphs have deadlines (timing constraints) and precedence relationships to satisfy. Our proposed algorithms, with low computational complexities, use the novel "path information track-and-update" scheme to distribute slack over tasks such that the overall energy consumption is minimized, and an observer mechanism to guarantee the application constraints. Our dynamic scheduling algorithm utilizes the results from the static scheduling algorithm and attempts to aggressively reduce the energy consumption. Simulations for the task graph for a typical BAN application show that our scheduling algorithms achieve better energy savings with less than 5% of the computational time, compared with the recent heterogenous multiprocessor scheduling algorithms.