Routing Based Ant Colony Optimization in Wireless Sensor Networks

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Dr. Anjali
Dr. Anjali
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Navpreet Kaur
Navpreet Kaur
α Lovely Professional University Lovely Professional University

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Routing Based Ant Colony Optimization in Wireless Sensor Networks

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Abstract

Wireless Sensor Networks (WSN’s) have become an important and challenging issue in last year. Wireless Sensor Networks consist of nodes with limited power are deployed to gather useful information from the field and send the gathered data to the users. In WSNs, it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. In this paper, we introduce a heuristic way to reduce energy consumption in WSNs routing process using Ant Colony Optimization. We introduce three Ant Colony Optimization algorithms, the Ant System, Ant Colony System and improved AS and their application in WSN routing process. The simulation results show that ACO is an effective way to reduce energy consumption and maximize WSN lifetime.

References

7 Cites in Article
  1. J.-Y Heo,J.-M Hong,Y.-K Cho (2009). EARQ: Energy aware routing for real-time and reliable communication in wireless industrial sensor networks.
  2. Marco Dorigo,Mauro Bimttari,Thomas Ant Colony Optimization Artificial Ants as a Computational Intelligence Technique.
  3. D Camara,Aaf Loureiro (2000). A novel routing algorithm for ad hoc networks.
  4. Mohammad Golshahi,Mohammad Mosleh,Mohammad Kheyrandish (2008). Implementing an ACO Routing Algorithm for AD-HOC Networks.
  5. Gianni Di,Caro,Frederick Ducatelle,Maria Luca,Gambardella (2005). SWARM INTELLIGENCE FOR ROUTING IN MOBILE AD HOC ETWORKS.
  6. Eric Bonabeau,Marco Dorigo,Guy Theraulaz (1999). Swarm Intelligence.
  7. T White,B Pagurek (1998). Towards multi-swarm problem solving in networks.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Anjali. 2013. \u201cRouting Based Ant Colony Optimization in Wireless Sensor Networks\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 13 (GJCST Volume 13 Issue E4): .

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Issue Cover
GJCST Volume 13 Issue E4
Pg. 35- 39
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Version of record

v1.2

Issue date

April 18, 2013

Language
en
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Published Article

Wireless Sensor Networks (WSN’s) have become an important and challenging issue in last year. Wireless Sensor Networks consist of nodes with limited power are deployed to gather useful information from the field and send the gathered data to the users. In WSNs, it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used in network routing. In this paper, we introduce a heuristic way to reduce energy consumption in WSNs routing process using Ant Colony Optimization. We introduce three Ant Colony Optimization algorithms, the Ant System, Ant Colony System and improved AS and their application in WSN routing process. The simulation results show that ACO is an effective way to reduce energy consumption and maximize WSN lifetime.

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Routing Based Ant Colony Optimization in Wireless Sensor Networks

Dr. Anjali
Dr. Anjali Lovely Professional University
Navpreet Kaur
Navpreet Kaur

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