Data Aggregation Using Genetic Algorithm in Wireless Sensor Network

A sensor network consists of one or more “sinks”. The sensors in the network act as “sources” which detect environmental events and push relevant data to the appropriate sinks. Sensors transmit information towards the sink if and when they detect the indicated phenomenon. Due to the redundancy present in the sensors’ readings, it is expected that communication approaches that take into account this redundancy, e.g., data aggregation and network processing. The main idea of the data aggregation and in-network processing approaches is to combine the data arriving from different sources (sensor nodes) at certain aggregation points (or simply aggregators) eliminate redundancies by performing simple processing at the aggregation points, and minimize the total amount of data transmission before forwarding data to the external BS (base station or sink).Genetic algorithm (GA) is used to create energy efficient data aggregation trees. During a chromosome, the gene index determines the node and the gene’s value identifies the parent node. Single-point crossover and mutation operators are used to create future generations. In this research work, by using various mutation of genetic algorithm a new algorithm is proposed for data aggregation in WSN.