A cross-layer approach to energy balancing in wireless sensor networks

Abstract

We consider a many-to-one real-time sensor network where sensing nodes are to deliver their measurements to a base station under a time constraint and with the overall target of minimizing the energy consumption at the sensing nodes. In wireless sensor networks, the unreliability of the links and the limitations of all resources bring considerable complications to routing. Even in the presence of static nodes, the channel conditions vary because of multipath fading effects due to the motion of people or objects in the environment, which modify the patterns of radio wave reflections. Also, sensing nodes are typically battery-powered, and ongoing maintenance may not be possible: the progressive reduction of the available energy needs to be factored in. The quality of the links and the remaining energy in the nodes are the primary factors that shape the network graph; link quality may be measured directly by most radios, whereas residual energy is related to the node battery voltage, which may be measured and fed into the microcontroller. These quantities may be used to form a cost function for the selection of the most efficient route. Moreover, the presence of a time constraint requires the network to favor routes over a short number of hops (a.k.a. the long-hop approach, in the sense that a small number of long hops is used) in order to minimize delay. Hop number information may be incorporated into the cost function to bias route selection toward minimum-delay routes. Thus, a crosslayer cost function is obtained, which includes raw hardware information (remaining energy), physical layer data (channel quality), and a routing layer metric (number of hops). A route selection scheme based on these principles intrinsically performs node energy control for the extension of the lifetime of the individual nodes and for the achievement of energy balancing in the network; intuitively, the long-hop approach permits the time-sharing of the critical area among more nodes. A novel, practical algorithm based on these principles is proposed with the constraints of the currently available hardware platforms in mind. Its benefits are investigated with the help of computer simulation and are illustrated with an actual hardware implementation using Berkeley motes.