A one-shot dynamic optimization methodology for wireless sensor networks

Wireless sensor networks (WSNs), consisting of autonomous sensor nodes, have emerged as ubiquitous networks which span diverse application domains (e.g., health care, logistics, defense) each with varying application requirements (e.g., lifetime, throughput). Sensor nodes possess tunable parameters (e.g., processor voltage, sensing frequency), which enable platform specialization for particular application requirements. WSN application design can be daunting for application developers, which are oftentimes not trained engineers (e.g., biologists, agriculturists) who wish to utilize the sensor-based systems within their given domain. Dynamic optimizations enable sensor-based platforms to tune parameters in-situ to automatically determine an operating state. However, rapidly changing application behavior and environmental stimuli necessitate a lightweight and highly responsive dynamic optimization methodology. In this paper, we propose One-Shot - A lightweight dynamic optimization methodology that determines initial tunable parameter settings to give a high-quality operating state in One-Shot for timecritical and highly constrained applications. Results reveal that One-Shot solution is within 5.92% of the optimal solution on average. To assist dynamic optimizations in determining an operating state, we propose an application metric estimation model to establish a relationship between application metrics (e.g., lifetime) and sensor-based platform parameters.