Wireless sensor networks are broadly used to gather and transfer the data with the help of sensors. Sensors nodes are not so expensive, but it works with limited energy resources. The deployment of such networks is done within various applications. These networks monitor the system or surroundings by measuring physical parameters, for example, moistness, weight and temperature WSNs are most appropriate for applications like natural life checking, military order, shrewd interchanges, modern quality control, movement observing, inspecting human heart rates, etc. The sensor nodes require less cost and power for providing communication in the network. This communication is established within limited range and the nodes get together to form a group. The strength of collaborative effort is leveraged by the sensor nodes which help in providing higher quality sensing within the time and the area provided. The nodes are self-organized in the forms of clusters such that they can complete the task assigned by users by collaborating with each other. There is no need of predefining the positions of the nodes within these networks. Thus, within various applications, the sensor nodes are deployed in order to provide communication. As there is huge quantity of data generated within the various sensing applications, the data is gathered together. This is done in order to reduce the energy consumption of the network. In order to continue simple computations and transmit only the data that is needed or processed partially, the processing abilities are required for the sensor nodes. To reduce the energy consumption of the wireless sensor networks whole network is divided into fixed size clusters and cluster heads are selected in each cluster on the basis of energy and distance. The cluster heads will transmit data to the base station. The cluster head which has maximum MAC value will first transmit data to base station and so on. The simulation is performed in NS2 and it has been analysed that proposed technique performs well in terms of energy consumption, throughput, packet loss and network lifetime.
wireless sensor network, clusters, sensors, load balancing, gateways, mac address and energy.