Energy-efficient cluster-based protocol using an adaptive data aggregative window function (A-DAWF) for wireless sensor networks

We present an adaptive data aggregative window function (A-DAWF) for a distributed sensor network model in which nodes store data in their attribute window functions, and provide non-correlated data towards the base station (BS). Unlike previous works, namely data collection or data gathering management systems, we propose a novel approach that aims to process temporal redundant techniques in sensor nodes as well as providing spatial redundant filtration methods in cluster-head (CH) nodes. In this regard, preliminary results show that A-DAWF can suppress up to 90% of temporal redundant data among the considered sensor nodes by an optimal threshold of the window sizes, and their spatial correlations in CH node by a maximum error threshold compared to either periodic or a continuous data transmission system.