Dynamic Profiling and Optimization Methodologies for Sensor Networks

This chapter describes methods aimed at alleviating some of the complexities associated with sensor-based system design through the use of computer-aided design techniques. It presents a dynamic profiling and optimization platform (DPOP) capable of observing application-level behavior and dynamically tuning the underlying platform accordingly. Dynamic optimization relies upon accurate profiling results collected at runtime. There exists much research in the area of dynamic optimizations; however, most previous work has focused on the processor or memory in computer systems. Within the DPOP environment, dynamically profiling a sensor-based application requires profiling methods to be incorporated within each node to monitor the execution behavior for individual sensor nodes. The chapter shows the per-node dynamic optimization process, which is orchestrated by the dynamic optimization controller. The process consists of two operating modes: the one-shot mode, wherein the sensor-node operating state is directly determined, and the improvement mode, wherein the operating state is iteratively improved using an online optimization algorithm.