Clustering is one of the important techniques in Wireless Sensor Networks (WSNs). In this paper introduce Double Cluster Head Model (DCHM) for secure and accurate data fusion in WSNs. Data fusion is used to reduce the traffic load and conserves energy of the sensors. In this clustering technique each cluster has two Cluster Heads (CHs) and they are assuming to be trust. After clustering each sensor nodes needs to maintain a reputation and trust table which is used to find the compromised nodes. Each CH perform the data fusion process independently and its sends the fused data to the base station. In this base station dissimilarity coefficient is computed and compared with threshold value which is preset by the users. If the dissimilarity coefficient exceeds the threshold, the CHs will be added to blacklist, and the CHs must be reelected by the sensor nodes in a cluster. And also feedback is sent from the base station to the reputation and trust system, which can helps to identify and delete the compromised sensor nodes. Through a series of extensive simulations, it can found that the DCHM performed very well in data fusion security and accuracy.

Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices that cooperatively sense physical or environmental conditions. Due to the non-uniform node deployment, the energy consumption among nodes are more imbalanced in cluster-based wireless sensor networks this factor will affect the network life time. Cluster-based routing and EADC algorithm through an efficient energy aware clustering algorithm is employed to avoid imbalance network distribution. Our proposed protocol EADC aims at minimizing the overall network overhead and energy expenditure associated with the multi hop data retrieval process while also ensuring balanced energy consumption among SNs and prolonged network life time .A optimal one-hop based selective node in building cluster structures consisted of member nodes that route their measured data to their assigned cluster head is identified to ensure efficient communication. The proposed routing algorithm increases forwarding tasks of the nodes in scarcely covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes and finally, achieves imbalanced among cluster head and improve the network life time.

No abstract