Study On Topology Control And Routing Optimization Of Wireless Sensor Networks

Multifunctional sensor with low loss is being developed quickly based on the progress of micro-electronics. Wireless Sensor Networks are composed of large quantity of micro-sensors deployed in monitoring fields, which are the multi-hop and self-organizing network systems via wireless communicating. These sensors are used to sense, collect, and process the information transmitted to the observer in monitoring fields.At present, many investigations are studied on routing,QoS, topolopy,network security and so on. This paper will pay attention to the WSN dynamic routing algorithm based on the clustering struct.In this paper,the background,the purpose and the implication of the topics are presented briefly. Then, we propose a cluster algorithm based on the tree structure. The algorithm begin with the Sink node and flooding to the whole net node. The nodes with more energy will have priority to be selected as the cluster head and relay node. Finding the leaf node in the net and finding the cluster head backwards from the leaf node. The group net information will begin with the leaf node and obtain a cluster tree, the sink node is the boot. Change the cluster node periodically to balance the energy consumption, prolong the survival. It bring forward some improvements in the position and energy of cluster head.To reduce the hotspot, the paper propose a clustering-based routing algorithm in wireless sensor networks with mobile sink(CRA). Under the CRA, Sink is moving in a circle around the region center and the area near this trajectory is set as buffering area, in which nodes are connected as backbone datalink. Data is firstly transmitted to the annular buffering area, and then reach the sink through multi-hop in the datalink. The paper also figure out the optimized location and area of the buffering area in order to minize the load of the nodes in the area. Furthermore, the paper propose CRA-1, which improve the original algorithm by control node density, for the purpose of evening the energy consumption of the whole network.