Energy management in battery-powered sensor networks with reconfigurable computing nodes

In this work we have investigated the benefits of using reconfigurable computing (RC) nodes in sensor networks. We assumed that several sensor nodes are deployed randomly in a field, to form a sensor network and each sensor in the network sends its data in the form of packets to a single energy-rich sink node. We also assumed that each sensor node has reconfigurable fabric which can be configured by downloading a bitstream. In contrast to the contemporary work in energy management for sensor networks, we use an accurate analytical battery model to simulate the battery consumption of each node in the network. We have written several simulation models to study various sensor network parameters when the underlying nodes are adaptive in nature instead of traditional, non-adaptive processor based, fixed implementation. As the remaining battery-capacity of our RC based node decreases, it changes its behavior by reconfiguring itself to lower powered implementations successively, thereby extending the sensor network lifetime as a whole. Our results indicate that the network life is increased by up to five times and the number of packets generated by the sensor nodes and received at the sink node more than quadrupled for RC based nodes when compared to fixed processor based node implementation.