Research On Hierarchical Routing Protocol For Wireless Sensor Networks Based On Genetic Algorithm

Wireless sensor networks (WSNs) combines system-on-chip (SoC), sensor technology and low-power consumption communication. All of the three technologies are developing very fast today. Usually WSNs consist of thousands of sensor nodes, these nodes are distributed randomly in those places that need to be monitored. In addition, these nodes can organize themselves in some specific approaches. WSNs are widely used in military, medical, and environmental monitoring and other fields. With the continuous development of technology, wireless sensor network technology will also show its mettle in the Internet of things.The capacity of batteries and computing of sensor nodes are restricted due to its size. How to prolong the survival time of WSNs is becoming more and more important these days. This paper focused at the Low-Energy Adaptive Clustering Hierarchy (LEACH) and combines it with Genetic Algorithm (GA). By using GA in route path, energy consumption can be reduced. The specific contents as follows:First, summed up a based on genetic algorithms for wireless sensor network routing protocol, which is a good solution to the limited energy and the randomly distributed and other characteristics of the wireless sensor network nodes, proposing a smart, dynamic, scalable routing transmission. It is a good way to get energy-efficient routing, and through energy balance the load to maximize the network lifetime and finally through simulation experiments verified the effectiveness of the genetic algorithms for wireless sensor network routing.Second, researching cluster-based routing protocol of WSN is the main part of this work. LEACH is selected to be the research target as the representative of the cluster-based routing protocols. We bring forward some improvements to LEACH protocol based on analyzing the shortages of it. The former LEACH algorithms for adapting clusters and rotating cluster head positions. In every round, the cluster heads are determined randomly. The improved LEACH periodically selects cluster heads according to their residual energy.Third, we optimized the process of CH selection, cluster formation and cluster routing. We use genetic algorithm during the time of cluster routing for finding the best route path which can reduce energy consumption. At last author stimulated the improved algorithm with LEACH and other algorithms to testify the effectiveness of new algorithm.