Localized Delay-bounded and Energy-efficient Data Aggregation in Low-traffic Request-driven Wireless Sensor and Actor Networks

We propose a localized Delay-bounded and Energy-efficient Data Aggregation scheme (DEDA) for wireless sensor and actor networks that are modeled as undirected graphs (URG). The scheme is based on a novel concept of Desired Hop Progress (DHP) and designed for low-traffic, request-driven network scenarios, where delay is proportional to hop count [10]. It builds a local minimal spanning tree (LMST) sub-graph of the network with links weighted by transmission powers. Using edges from LMST, it constructs a shortest path (thus energy-efficient) tree rooted at actor (sink) for data aggregation. The tree is used as is if it generates acceptable delay. Otherwise, it is adjusted by replacing LMST sub-paths with URG edges. The adjustment is done locally, according to the DHP value at each node, with hop count reduction corresponding to the delay allowance per hop (ratio of current LMST delay over maximal allowed one). Through extensive simulation, we show that DEDA may save 25-75% energy per node on average and extend up to 150% network life, depending on network conditions, in comparison with the only existing competing localized solution [11].