Published Paper Details:

Wireless Sensor Networks are becoming more and more popular as cost of sensor gets cheaper. A wireless sensor device is a battery-operated device, capable of sensing physical quantities or environmental conditions. They become more and more important for applications like security, traffic monitoring, agriculture, battlefield surveillance, and also used to measure air pressure, temperature, acceleration, etc. Sensors in networks are responsible for four major tasks: data aggregation, sending and receiving data, and in-network data processing. The sensor nodes communicate together by routing protocols. Many routing protocols, data dissemination protocols and power management protocols have been specifically designed for WSNs where energy conservation is an important design issue to increase the lifetime of networks. The reliable routing of packets from sensor node to base station is the important task for the network. Redundant data can increase the size of message. This Increase communication cost, energy consumption and decrease the lifetime. In response to this challenge, over the last few years there have been increasing efforts to minimize energy consumption via new algorithms and techniques in different layers of the WSN, including the hardware layer (i.e. sensing, processing, and transmission), network layer (i.e. Protocols, routing) and application layer. Data aggregation by clustering is an important method to reduce the energy consumption of sensor nodes and improve the bandwidth utilization. The selection of particular routing protocols in network layer depends on the application and network architecture. Much research focuses on a single aspect of WSNs, In this project an energy driven architecture is designed for minimizing the total energy consumption and lossless data aggregation by clustering using Particle swarm optimization and results are compared with existing algorithms.