Energy Management for Time-Critical Energy Harvesting Wireless Sensor Networks

As Cyber-Physical Systems (CPSs) evolve they will be increasingly relied on to support time-critical monitoring and control activities. Further, many CPSs that utilize Wireless Sensor Networking (WSN) technologies require energy harvesting methods to extend their lifetimes. For this important system class, there are currently no effective approaches that balance system lifetime with system performance under both normal and emergency situations. To address this problem, we present a set of Harvesting Aware Speed Selection (HASS) algorithms. We use an epoch-based architecture to dynamically adjust CPU frequencies and radio transmit speeds of sensor nodes, hence regulate their power consumption. The objective is to maximize the minimum energy reserve over any node in the network, while meeting application's end-to-end deadlines. Through this objective we ensures highly resilient performance under emergency or fault-driven situation. Through extensive simulations, we show that our algorithms yield significantly higher energy reserves than the approaches without speed and power control.