Enhanced Load Balanced Clustering Technique for VANET Using Location Aware Genetic Algorithm

The vehicular Adhoc Network has unique charac-teristics of frequent topology changes, traffic rule-based node movement, and speculative travel pattern. It leads to stochastic unstable nature in forming clusters. re-liable routing process load balancing are essential improve the network lifetime. Cluster formation is used split into small structures. reduced size accumulating information quickly. Due absence centralised management, there a pitfall man-agement optimal resource allocation, resulting ineffective routing. Hence, it necessary develop an effective clustering algorithm for VANET. In this paper, Genetic Algorithm (GA) Dynamic Programming (DP) designing load-balanced proposed Angular Zone Augmented Elitism-Based Im-migrants GA (AZEIGA) elitism-based immigrants deal with population DP store out-come old environments. AZEIGA ensures nodes, which prolongs Experimental results show that works appreciably well homogeneous class simulation proves gave better perfor-mance packet delivery, lifetime, average de-lay, routing, overhead.