The clustering framework on exploring spatio-temporal correlations in wireless sensor networks

In this paper, we propose a clustering framework on exploring spatio-temporal correlations in wireless sensor networks. It integrates the advantages of clustering technique and spatio-temporal correlations in wireless sensor network. It can reduce the amount of messages sent in the network a lot and assure the average relative error is not exceeding a tolerant error bound. The optimized energy-balanced routing algorithm we propose can prolong the lifetime of the network by ensuring the energy of the nodes in the routing path must not lower than a threshold. Simulation results show that our framework is energy-efficient and can avoid the impact of unexpected data effectively.