Adaptive Low Power Listening for Wireless Sensor Networks
IEEE Transactions on Mobile Computing
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Wireless ad hoc networks and sensor networks are emerging as new network classes that differ considerably from conventional wired or wireless networks. The distinguishing characteristic of ad hoc and sensor networks is the lack of deployed infrastructure, which poses the design challenge of distributing network management among the nodes. Nodes in ad hoc and sensor networks also have limited resources, so the distributed algorithms and protocols that manage network behavior must also enable fine-grained optimization at the resource-limited nodes. In addition, ad hoc and sensor networks have a wide range of potential applications, each of which requires custom performance guarantees, suggesting the need for a flexible methodology to optimize network behavior. This dissertation presents a flexible cross-layer framework for optimizing the performance of ad hoc and sensor networks that enables each node to greedily and locally optimize its behavior in order to achieve a global performance goal. The framework provides a customizable definition of node states and it enables the network designer to select the network mechanisms at any layer of the communication stack that require optimization. The framework's applicability and optimization potential are validated through three diverse case studies: (1) minimization of energy consumption in a sensor network test-bed using radio frequency signals; (2) maximization of throughput and fairness, and reduction of control overhead and link setup latency in an ultra wide band ad hoc network; and (3) maximization of battery lifetime and minimization of power consumption in an acoustic underwater sensor network. Each case study adopts a customized version of the framework by tailoring state definitions and by defining mechanisms that require optimization in accordance with the case study's performance requirements. In all cases, the framework yields significant improvement in network performance.