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Energy Efficient agent based approach for data aggregation in wireless sensor network

Author(s): Pranavi Tayal | Hardwari Lal Mandoria | Himanshu Chanyal

Journal: International Journal of Wired and Wireless Communications
ISSN 2319-9512

Volume: 2;
Issue: 1;
Start page: 31;
Date: 2013;
Original page

Keywords: data aggregation | mobile agent | itinerary planning | wireless sensor networks

A sensor network is composed of vast number of tiny sensor in a limited area. Each sensor is defined with some energy parameters and the energy based constraints. According to these constraints, as the communication is performed, each participating node loses some amount of energy.  Multicast and Broadcast communication are the basic communication requirements of a sensor network. But such kind of communication increases the network traffic extensively as well as gives large amount of energy loss. Data aggregation provides the solution to this problem by combining the multiple communications in single communication path. Data aggregation is one of the major communication approach in which multiple sources are sending data to single sink. In this present work, an agent based approach is defined to generate the effective aggregative path so that the network life and communication will be improved. Wireless Sensor network is an ad hoc network of tiny sensors. Each sensor is defined with some energy and floating nature. As the data is transferred over the network each sensor spends some energy in receiving data, sending data and forwarding data. Because of this network life depends on how much energy spend in each transmission. Due to the energy constraints, wireless sensors usually have a limited transmission range, making multi hop data routing towards the PN (processing node) more energy efficient than direct transmission (one hop). A primary design goal for wireless sensor networks is to use the energy efficiently. The proposed system will improve the network communication.The presented work is implemented in NS2 environment and obtained results shows that the presented work has improved the network throughput extensively and reduced the network delay and the data loss.
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