AWARE: Activity AWARE network clustering for wireless sensor networks

Both energy efficiency and high data relevancy are crucial for wireless sensor network applications. Network clustering and event-driven protocols are two main approaches typically used to fulfill those requirements. Existing techniques are either focused only on performance of clusterheads or too restricted to specific applications; however, few of previous work took advantage of the combination of both approaches. In this paper, we formalize the combined problem of network clustering in an event-driven manner, show its NP-Completeness and present an innovative distributed heuristic solution. We hereby propose AWARE, an event-driven and energy-aware network clustering technique. AWARE groups highly active nodes together and thus make clusterheads report more efficiently with only relevant data. This approach guarantees the benefit of both reduced energy consumption and aggregated highly relevant data. Furthermore, AWARE is not only able to recover from node failures for in-network communication, but also provides a communication structure for high level services. We theoretically prove that AWARE indeed provides the solution to the problem, as it completes in constant time, forms connected clusters and can recover from node failures. Finally, our extensive performance studies also validate the effectiveness and efficiency of AWARE.