Spatio-temporal correlation: theory and applications for wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: In memroy of Olga Casals
IEEE Transactions on Parallel and Distributed Systems
Spatial Data Correlation Based Clustering Algorithms for Wireless Sensor Networks
ICICIC '08 Proceedings of the 2008 3rd International Conference on Innovative Computing Information and Control
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
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In wireless sensor networks (WSNs), the sensor nodes that locate near often sense the similar data, however, transmitting the repeated or redundant data often cause unnecessary energy consumption. Aiming at this point, this paper firstly proposes a grid-based spatial correlation clustering (GSCC) method which clusters the sensor nodes according to data correlation. According to GSCC, in the same cluster the member nodes have high similarity. Based on GSCC, then this paper proposes a spatial correlation clustering approximation framework (SCCAF). SCCAF can largely save networks' energy by which the cluster head estimates the data of its member nodes provided that approximation value is in the allowable error range. Experiments prove that not only SCCAF based on GSCC method can prolong the lifetime ofthe sensor networks compared with LEACH but also SCCAF guarantees more accuracy than CASA (clustering-based approximate scheme for data aggregation) which is a previous approximation scheme.