Clustering Algorithm Research Based On Trust In Wireless Sensor Networks

Wireless sensor networks are network system comprised by a large number of micro sensor nodes using wireless communication patterns. Users can monitor the environment by these nodes which can sense the physical information and forward the data to the users. Due to the wide application and research value, Wireless sensor networks are becoming one of the most heat technologies nowadays.As the main technology used in wireless sensor networks, layer structure draws the attention of the researchers. Two layer structures are used in this paper. In the two layer structure, normal sense nodes make up the first layer and cluster heads make up the second layer. Usually in each cluster, normal sensor nodes are responsible to sense the environment and forward the data to the cluster head. The cluster head are responsible to gather the data from all the nodes in the cluster and forward the syncretic result to the end users. Besides, cluster head also responsible for the management and monitoring of the normal sense nodes in the cluster. In this way, layer structure in the WSNs can be useful for the management of the nodes and energy efficiency.Many clustering scheme have been proposed in literature and do have given much development for the energy efficiency and increasing the creditability of the cluster head. But most of these researches didn’t get any improvement in balancing the developing the energy efficiency and creditability of the cluster head. In this paper, a more reasonable clustering scheme aimed to saving energy and ensure the creditability of cluster head will be presented.Based on the wide research on the latest achievement, Considering creditability and residual energy of cluster head, clustering algorithm using cloud theory and particle swarm optimization have been introduced in this paper.The specific research will be introduced as follows:1. The second chapter gives the modified trust management model in wireless sensor networks. Trust management model can helped to identify and exclude the malicious and compromised nodes by which can prevent the inner attack. Many trust models have been presented and have gain several improvement. A model which will be not only simple to implement but also ensure the accuracy of trust values is presented.2. The third chapter gives the novel selection framework considering trust and residual energy based on trust. According to the random and fuzziness of the trust of the nodes in networks, it is much more reasonable to use cloud theory which combine the statistics and fuzzy theory to present the trust values.3. The fourth chapter gives the clustering algorithm using particle swarm optimization. From the research experience about the application of the particle swarm optimization in wireless sensor networks, it can be useful to gain the optimized solutions.