Research On Topology Control For Wireless Sensor Networks Based On Genetic Strategy

Wireless sensor network is composed of a large number of cheap wireless sensor nodes with limited energy, the network has self-organization, distributed characteristics. With the rapid development of wireless communications, sensors and embedded system, wireless sensor networks has been widely used, especially in the field of environmental monitoring, smart home, and industrial monitoring applications. Topology control is one of the core issues in wireless sensor networks. Reasonable network topology is of paramount importance in wireless sensor networks to reduce energy consumption of network nodes and prolong the lifetime of network and increase the efficiency of routing protocols.In this paper, some classical topology control algorithm for wireless sensor networks and the genetic algorithm had been researched, then the genetic algorithm and the wireless sensor network topology control were combined together. From the perspective of power control, a k-connected fault-tolerant topology control algorithm based on GA had been proposed. The algorithm takes k-connected of network as constraint and node energy consumption as optimization target. The transmitter radius of network nodes was discovered by genetic algorithms. The experiment results showed that the algorithm can not only greatly reduce the redundant link, reducing the energy consumption of nodes, but also ensure the connectivity of the network, the network topology can be maintained in an optimal manner.From the perspective of hierarchical control, a clustering nodes sleep scheduling strategy with genetic algorithm in wireless sensor networks was proposed. All nodes would be divided into several clusters based on information of node location and energy of node by using genetic algorithm in the first stage. Then Schedule nodes in the cluster with nodes remained energy, cluster coverage rate and overlap area after cluster. The network topology would be optimized at second stage. The experimental results showed that the algorithm can balance the node energy consumption effectively and prolong the lifetime of network compared with LEACH and LEACH-GAHS.