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Energy is a valuable resource in wireless sensor networks (WSNs). The status of energy consumption should be continuously monitored after network deployment. The information about energy status can be used to early notify both sensor nodes and network deployers about resource depletion in some parts of the network. It can also be used to perform energy-efficient routing in WSNs. In this paper, we...
Wireless sensor networks may be deployed in an environment the intrinsic pattern of data is unknown and may not be amenable to statistical aggregation techniques. Moreover, the dynamic nature of the environment may generate large amount data which may be highly similar with few data values that may be noisy or may indicate interesting observation. The present work proposes resonance based clustering...
The high cost of communication vis-a-vis computation cost necessitates efficient aggregation in wireless sensor networks. This paper proposes and evaluates two different clustering techniques, FAMNN and DBA. The first approach based on adaptive resonance theory whereas the second approach is based on density based clustering of data. The first technique, FAMNN is based on fuzzy ART and fuzzy ARTMAP...
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