TCACWCA: transmission and collusion aware clustering with enhanced weight clustering algorithm for mobile ad hoc networks

In case of MANET the routing acts a superior role in the mobile ad-hoc network environment so as to guarantee the consistent communication amongst the source and the destination nodes. On the other hand routing in the MANET environment will have a number of challenges because of dynamic behavior of mobile nodes exist in the environment. Mobility behavior of mobile nodes will bring about path link breakages that needs novel route for the data transmission to be kept up to date or set up frequently. This behavior causes network failure. It results in more computational overhead by forwarding hello message to come across the novel nodes gone into the environment. With the purpose of overwhelming these issues, the novel approach is presented, that is to say transmission and collusion aware clustering with enhanced weight clustering algorithm (TCAC–WCA) so as to decrease the risk of the forwarding hello packets at every time clustering. In this study, the improved weight clustering algorithm is utilized to form the cluster dependent upon the weight on the node.The Transmission Range Clustering Algorithm (TRCA)is utilized to eradicate the needless node that there are not presented inside the transmission range and likewise test out the link stability of the node. By means of computing the trust level, the collusion is noticed in the wireless link. The presented TCAC–WCA is tested dependent upon two metric called expected transmission count (ETX) or path encounter rate (PER) for every identified state with the aim of attaining the ideal routing performance for diverse network conditions (that is to say Static or mobile). Similarly the route node dictionary is built dependent upon the ETX and PER metric. The complete assessment of the presented research technique is accomplished in NS2 simulation environment through which it is shown that the presented research technique results in giving improved outcome compared to the previous research techniques.