Efficient algorithm for serial data fusion in wireless sensor networks

Although Wireless Sensor Networks (WSNs) are capable of generating a huge amount of data, the ultimate objective of the underlying applications/end-users is to derive an estimate of a parameter or function of interest through queries sent to nodes containing raw data. The way these queries are handled by the network has a deep impact on its overall performances ( e.g., required communications, consumed energy, etc.). Among the numerous centralized and distributed approaches addressing this issue, serial ones have shown an interesting improvements in terms of reducing communication needed for each query and hence reducing required energy. Nevertheless, serial approaches suffer two main drawbacks: (a) they require to construct a path passing through all nodes of the network (which is known to be a NP-Complete problem) and (b) they experience poor scalability. In this paper, we investigate these issues by proposing a novel localized serial approach, called Peeling Algorithm (PA). The proposed approach, because of its localized nature (i.e., no extra-information is needed rather than what it is already available at each node), has shown better support for scalability while reducing significantly needed communications to accomplish a query. The extensive simulation evaluations we made have confirmed the effectiveness of our proposed approach in comparison to other serial approaches. We also provide in this paper formal proofs of its correctness i.e., our distributed approach terminates (free of looping) and visits all connected nodes in the network.