Data Fusion with Desired Reliability in Wireless Sensor Networks

Energy-efficient and reliable transmission of sensory information is a key problem in wireless sensor networks. To save more energy, in-network processing such as data fusion is a widely used technique, which, however, may often lead to unbalanced information among nodes in the data fusion tree. Traditional schemes aim at providing reliable transmission to individual data packets from source node to the sink, but seldom offer the desired reliability to a data fusion tree. In this paper, we explore the problem of Minimum Energy Reliable Information Gathering (MERIG) when performing data fusion. By adaptively using redundant transmission on fusion routes without acknowledgments, packets with more information are delivered with higher reliability. For different data fusion topologies, such as star, chain, and tree, we provide optimal solutions to compute the number of transmissions for each node. We also propose practical, distributed approximation algorithms for chain and tree topologies. Analytical proofs and simulation results show that energy-efficient information reliability can be guaranteed in an unreliable wireless environment with the help of our proposed schemes.