Research On GA Based Routing And Data Aggregation Algorithms For WSN

Wireless Sensor network(WSN), which is made by the convergence of sensor, nested computation, networks and wireless communication technologies, introduces a novel technology about acquiring and processing information. It can inspect, apperceive and collect the information of kinds of environments and inspected objects, process the information and send the information to the needed users. WSN becomes a new research area of modern communication technology. Both academia and industries are very interested in it.The numbers of sensor node in WSN are numerous and single node is extraordinarily limited in resource. The all-important aim of designing routing protocol of WSN is to reduce the overall energy dissipated in the network and to maximize the network lifetime. By data aggregating it can reduce the number of transmissions of the network, gain exact information and increase the data collecting efficiency. Therefore, kinds of algorithms of data aggregation have been put forward. In this thesis, the NPC problem in joint of data aggregation and routing is analyzed, and an approximate solution based on GA called GARDA is produced.In this thesis, sensor nodes are randomly deployed in the sensor field. First, the network area is divided into fixed and equal square zones in order to reduce the energy consumption in clustering; second, a node j∈l which has higher remaining energy( E j) and has served fewer number of time ( timesc j), will be eligible to act as the CH (cluster head) node in that zone, so it makes the nodes'energy consumption in the cluster balanced; in order to minimize the network energy consumption a NPC problem jointed of data aggregation and routing is brought forward, an ILP solution is analyzed in theory. However, the fact that there are so many parameters in the ILP algorithm leads to high costs in computing, so it is hard to realized and approximate solutions are usually introduced. The genetic algorithm based on natural selection and heredity and mutation is a global searching algorithm, can be used in NPC problem of global optimization. The GARDA algorithm based on GA is used in this thesis to solve this NPC problem and realize the data aggregation in network layer. The simulating test of this algorithm proved that this algorithm can prolong the network lifetime effectively and reduce the energy consumption of the network.