IMPROVED SCHEME FOR CLUSTER BASED FAULT TOLERANT DATA AGGREGATION IN WIRELESS SENSOR NETWORKS

Abstract

Wireless Sensor Networks (WSNs) are used widely in many mission critical applications like battlefield surveillance, environmental monitoring, forest fire monitoring etc. A lot of research is being done to reduce the energy consumption, enhance the network lifetime and fault tolerance capability of WSNs. In this paper, we propose an energy aware routing algorithm for cluster based WSNs along with an ANFIS estimator based data aggregation scheme called Neuro-Fuzzy Optimization Model (ANFIS-NFO) for the design of fault-tolerant. The algorithm is based on a clever strategy of cluster head (CH) selection, residual energy of the CHs and the intra-cluster distance for cluster formation. To facilitate data routing, a directed virtual backbone of CHs is constructed which is rooted at the sink. The proposed algorithm is also shown to balance energy consumption of the CHs during data routing process. We prove that the algorithm achieves constant message and linear time complexity and they pro-actively identify the faulty CHs by the application of the proposed ANFIS estimator and perform inter-cluster fault tolerant data aggregation.