Energy Efficient Hierarchical clustering for sensor networks

In the development of various large-scale sensor systems, a particularly challenging problem is how to dynamically organize the sensor nodes into a wireless communication network and route sensed information from the field sensors to a remote base station. This work presents a new energy-efficient dynamic clustering technique for large-scale sensor networks. By monitoring the received signal about power from its neighboring nodes, each node estimates the number of active nodes in real time and computes its optimal probability of becoming a cluster head, so that the amount of energy spent in both intra- and inter-cluster communications can be minimized. Cluster head selection is an important problem in sensor networks. Cluster-based routing has been shown to be more energy efficient and increase the network lifetime through data aggregation. The goal is to select cluster heads that minimize transmission costs and energy usage. Based on the clustered architecture, this work proposes a Multi level Hierarchical Approach in Dynamic Clustering using Election Algorithm for the efficient Cluster Head selection and Dynamic Energy Efficient Hierarchical routing algorithm for energy efficient routing. When compare to existing work the Multi level Hierarchical Approach will work efficiently. The new clustering and routing algorithms will work efficiently and reduces the energy consumption of sensor nodes.