Research And Implementation Of Clustering Routing Protocols Based On Optimization Algorithm In Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been widely considered as one of the spot for the twenty-first century and consist of hundreds or thousands low-energy and multi-function sensors which form a network by wireless links. Nodes cooperatively transform particular information gathering in the sensing area to the user terminal by network. Sensors detect and monitor physical parameters or conditions, for example, temperature and light in air, ingredient and humility in soil and speed and director of the mobile object. The potential application included environment monitoring, military monitoring, health care application and industrial process control.Normally, there are five layers in wireless network protocol, application layer with special application, transport layer with logical link, network layer with routing MAC layer with medium access, and physical layer with data link. Sensors nodes are battery powered and thus have very limited energy capacity. To prolong the operational lifetime of a sensor network, energy efficiency should be considered in every aspect of sensor network design, not only hardware and software, but also network architectures and protocols.In this paper, we have adopted a centralized clustering approach based on artificial bee colony algorithm which simulating the intelligent foraging behavior of honey bee swarms. This approach selects the optimal cluster head by choosing different fitness function which involves the consumed energy and the residue energy. It can effectively improve energy efficiency, balanced energy load, improve number of Surviving node and prolong the network lifetime. Based on the above algorithm, this paper proposed a protocol based on artificial bee colony optimization algorithm and assistant cluster head. this protocol add an assistant cluster head mechanism. The primary cluster head gather information from cluster members and communication with the assistant cluster head and then the assistant cluster head transfer data to the base station. Without change the Time Complexity and joining the mechanism of the assistant cluster head into the optimization process, this improvement effectively balance the network energy and prolong the lifetime of the network by making the optimal clustering cluster head stay longer. Comparing with the simulation of different protocols, the results validate the efficiency of the two cluster head approach.