Data Density Correlation Degree Clustering Algorithm for Multiple Correlated Sensor Networks using Fuzzy Logic

Abstract

Wireless Sensor Network (WSN) is the collection of several sensor nodes which are able to send their sensed data to base station. In dense WSN, consecutive observations obtained by sensors are spatial as well as temporally correlated in applications that involve the observation of the variation of a physical phenomenon. These sensor nodes are battery driven, therefore an efficient utilization of power is essential in order to reduce data traffic inside sensor networks and thus reduce amount of data that need to send to base station for enhancing the network lifetime. For this reason data aggregation is used. The correlation degree gives a correlation measurement that measures the correlation between a sensor node's data and its neighboring sensor nodes' data. The resulting representative data obtained using the proposed methods have a lower data distortion than those obtained earlier. Also, to construct an energy balanced network in data transmitting process, the energy of every sensor nodes should be considered and Fuzzy Logic is also used to determine an optimal routing path from the source to the destination by maintaining the highest remaining battery power, minimum traffic loads and minimum number of hops.
DOI: 10.17762/ijritcc2321-8169.160496