(untitled) (Global Journal of Advanced Engineering Technologies and Sciences, 2016)
The WSN is built of "nodes" from a few to several hundreds or even thousands, where each node is connected to one (or sometimes several) sensors. Each such sensor network node has typically several parts: a radio transceiver with an internal antenna or connection to an external antenna, a microcontroller, an electronic circuit for interfacing with the sensors and an energy source, usually a battery or an embedded form of energy harvesting. A sensor node might vary in size from that of a shoebox down to the size of a grain of dust, although functioning "motes" of genuine microscopic dimensions have yet to be created. The cost of sensor nodes is similarly variable, ranging from a few to hundreds of dollars, depending on the complexity of the individual sensor nodes. Size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and communications bandwidth. The topology of the WSNs can vary from a simple star network to an advanced multihop wireless mesh network. In this project are using fuzzy clustering, k-mean and self-organizing map (SOM) based clustering method. It is observed that overhead in cluster based protocol is not much dependent upon update time. Simulation a result indicates that a cluster based protocol has low communication overheads compared with the velocity based protocol. In the simulation result we consider main approaches Clustering technique (SOM, Fuzzy, K-Means), differentdifferent numbers of node (50,100 and 150) with 5 cluster. The simulation performance analysis on the based comparison of average energy consumption. The result shown between communications overhead versus velocity and percentage decay rate of energy for WSN versus Velocity.