Scalable and Efficient Clustering for Fingerprint Based Positionings

Wireless sensor network generate hotspots because of heavy traffic load at certain locations. Nodes in hotspots lose energy resources quickly and disrupt network services. The Cluster head (CH) gets more burdens in gathering and relaying information. Relay load on CH gets increased as distance to sink decrease. CH role is articulated across all nodes to balance traffic load and energy consumption. The existing work presented distributed energy efficient clustering algorithm that determine suitable cluster size based on the listed factors. Hop distance to data sink, Equalization of node lifetime, reduced energy consumption levels. This design energy efficient multi-hop data collection protocol is to calculate end to end energy consumption. The proposed scheme is to present Mobility Aware cluster head selection in the hotspots of WSN. This calculates node reputation to have better cluster head. Ranking is made based on both node reputation and its mobility rate. This also increases the clustering efficiency in terms of cooperativeness and mobility of sensor nodes. However, certain sensor nodes have high mobility. In addition certain nodes unwilling to serve the network, the proposal present Mobility Aware Reputation Node Ranking (MARNR) technique to improve the efficiency of clustering at hot spot regions. MARNR identifies the senor nodes mobility rate. Each node serving the region as cluster is identified from the cache. This ensures the node should have minimal mobility threshold and high cluster head rank probability. Simulation is carried out to evaluate performance of EC in terms of Network life time, Energy consumption, Mobility rate, CH ranking, Node reputation Count, Hot spot density, Cluster Size.