A Routing Algorithm Based On Clusters And Balanced Use Of Energy For Wireless Sensor Network

Wireless Sensor networks are composed of large, small, low-cost sensors, which collect and disseminate environmental data. Wireless sensor networks facilitate monitoring and controlling of physical environments from remote locations with better accuracy. Sensor nodes have various energy and computational constraints because of their inexpensive nature and ad hoc method of deployment. Considerable research has been focused at overcoming these deficiencies through more energy efficient routing, localization algorithms and system design.In this thesis, routing algorithms designed by some researchers are introduced. However, these methods do not use data correlation or a similar heuristic to find an optimal route for compressing the data during aggregation. Other researchers provide a simple distributed algorithm to implement the DSC. The decoding error is unavoidable by this method although error detection and correction techniques can deal with such errors. Most of algorithms are severely hampered by scaling in large wireless networks, both in terms of energy consumption and latency costs.In this thesis, a compression-centric data collection algorithm is used in wireless sensor networks to calculate the energy consumption of a cluster in process of transmission. The algorithm relies on the construction of a Minimum Cost Tree (MCT), using neighbor data correlation as the optimization heuristic along the tree. By selecting routes that traverse nodes with higher degrees of data correlation, it is probable to achieve superior compression. An algorithm which is based on clusters of balanced use is presented. Two aspects of the problem are also be focused on: (i) how does one estimate the number of clusters needed to efficiently utilize data correlation of sensors for a general sensor network, and (ii), given the number of clusters, how does one pick the cluster-heads to cover the sensor network efficiently.Simulation, by NS2, is used to evaluate the performance of the algorithm proposed compared to exhaustively found optimal solutions, and results show that our algorithm achieves significant improvement in power consumption. And the simulation is divided into three groups. The more amount of transmission is, the more energy of saving is. Through the six schemes, the purpose of prolonging the lifetime of wireless sensor networks can be achieved. It means that routing based on clusters and energy of balanced use is an efficient routing algorithm.