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Balanced Energy Consumption Approach Based on Ant Colony in Wireless Sensor Networks

Balanced Energy Consumption Approach Based on Ant Colony in Wireless Sensor Networks

Sahabul Alam, Debashis De
Copyright: © 2017 |Pages: 27
ISBN13: 9781522517597|ISBN10: 1522517596|EISBN13: 9781522517603
DOI: 10.4018/978-1-5225-1759-7.ch035
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MLA

Alam, Sahabul, and Debashis De. "Balanced Energy Consumption Approach Based on Ant Colony in Wireless Sensor Networks." Artificial Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 861-887. https://doi.org/10.4018/978-1-5225-1759-7.ch035

APA

Alam, S. & De, D. (2017). Balanced Energy Consumption Approach Based on Ant Colony in Wireless Sensor Networks. In I. Management Association (Ed.), Artificial Intelligence: Concepts, Methodologies, Tools, and Applications (pp. 861-887). IGI Global. https://doi.org/10.4018/978-1-5225-1759-7.ch035

Chicago

Alam, Sahabul, and Debashis De. "Balanced Energy Consumption Approach Based on Ant Colony in Wireless Sensor Networks." In Artificial Intelligence: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 861-887. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1759-7.ch035

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Abstract

Now a days Wireless Sensor Networks (WSNs) have grown rapidly due to advancement of information technology. Sensor nodes are deployed over the field for collecting useful information. Sensor nodes have limited battery power and bandwidth. As a result it is critical for planning energy efficient protocols in WSNs. It is necessary to transfer and gather information in optimized way to reduce the energy dissipation. Ant Colony Optimization (ACO) is already proved to be better technique to optimize the network routing protocols in WSNs. Ant based routing can have significant role to extend the network life time and balance energy consumption in WSNs. In this chapter wireless sensor network architecture, routing factors of wireless sensor networks, computational intelligence technique, ant colony algorithm and ant colony based balanced energy consumption approaches in wireless sensor network have been discussed.

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