Energy Efficient Between Nodes For Wireless Sensor Network

Wireless sensor network (WSN) consists of a large number of embedded nodes with sensing, capability of perception, computing and communication ability through self-organization. Its purpose is to cooperatively sense, collect and process sensing information. Wireless sensor network has attracted the attention of academia and industry. They are widely used in military and civil fields.In wireless sensor network, due to the limitation of the sensor node itself, usually powered by battery, the energy is very limited, and it could’t add energy when it is using. Therefor, how to efficiently save the energy of sensor node and maximize the network survival time is very important. In this paper, we use the method of balancing the average energy consumption per unit time between nodes to improve the lifetime of network and maximum efficiency of node.First of all, this paper proposes a corona-based network partitioning algorithm. We assume the network is divided into a plurality of zones of variable width, the commumication radius of all nodes in the network can be adjusted. Nodes in the same corona have the commumication radius equal to the width of corona. Calculation expression is given in arbitrary ring nodes in unit time average energy consumption through the derivation. Data shows, this algorithm greatly improves the lifetime of network, and is a good solution to optimize the energy consumption between the nodes.Secondly, based on the last algorithm, we present a node non-uniform deployment algorithm in wireless sensor networks. With the results of last algorithm, we proved that only based on all the width of the coronas equaling to the width of innermost corona for minimizing the energy consumption of the nodes per unit time in WSN. The ratio of adjacent zone node energy consumption and the ratio of the number of nodes are givined. According to this formula, we can carry out the nodes of the network with non-uniform deployment. Comparing to last algorithm, this algorithm can effectively improve the lifetime network with adjusting the distribution of sensing nodes in the network.