On the design of static and dynamic energy-aware task mapping algorithms for body area networks

In this paper we propose novel energy-aware task-mapping algorithms -static and dynamic, for body area networks (BANs). These algorithms map tasks onto a heterogeneous wireless system of sensor nodes such that the tasks meet the deadline and also the energy consumption is a minimum. The static mapping algorithm uses the max-flow min-cut algorithm to obtain an efficient initial mapping. Then the dynamic algorithm uses the scaling factor criteria to improve the mapping and works in an iterative fashion to improve the quality of mapping. We illustrate the workings of these algorithms via examples for the ease of understanding.