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Energy-efficient and location-aware ant colony based routing algorithms for wireless sensor networks

Published: 12 July 2011 Publication History

Abstract

In recent years, advances in miniaturization, low-power circuit design, simple, low power, yet reasonably efficient wireless communication equipment, and improved small-scale energy supplies have combined with reduced manufacturing costs to make a new technological vision possible, Wireless Sensor Networks (WSN). As WSN are still a young research field, much activity is still on-going to solve many open issues. One is the data routing problem. As the size of the network increases, this problem becomes more complex due the amount of sensor nodes in the network. The meta-heuristic Ant Colony Optimization (ACO) has been proposed to solve this issue. ACO based routing algorithms can add a significant contribution to assist in the maximisation of the network lifetime and in the minimisation of the latency in data transmissions, but this is only possible by means of an adaptable and balanced algorithm that takes into account the WSN main restrictions, for example, memory and power supply. A comparison of two ACO based routing algorithms for WSN is presented, taking into account current amounts of energy consumption under a WSN scenario proposed in this work. Furthermore, a new routing algorithm is defined.

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Cited By

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  • (2022)Energy Optimization and Optimal Routing Protocol in Wireless Sensor Networks2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA)10.1109/ICIRCA54612.2022.9985549(484-489)Online publication date: 21-Sep-2022
  • (2018)Event Based Clustering Localized Energy Efficient Ant Colony Optimization (EBC_LEE-ACO) for Performance Enhancement of Wireless Sensor NetworkEngineering, Technology & Applied Science Research10.48084/etasr.21218:4(3177-3183)Online publication date: 18-Aug-2018
  • (2013)Using Ant Colony Agentsfor Designing Energy-Efficient Protocols for Wireless Ad Hoc and Sensor NetworksHandbook of Green Information and Communication Systems10.1016/B978-0-12-415844-3.00024-3(611-629)Online publication date: 2013
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cover image ACM Conferences
GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation
July 2011
2140 pages
ISBN:9781450305570
DOI:10.1145/2001576
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 July 2011

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Author Tags

  1. ant colony optimization (ACO)
  2. network lifetime
  3. routing algorithms
  4. wireless sensor networks (WSN)

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2022)Energy Optimization and Optimal Routing Protocol in Wireless Sensor Networks2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA)10.1109/ICIRCA54612.2022.9985549(484-489)Online publication date: 21-Sep-2022
  • (2018)Event Based Clustering Localized Energy Efficient Ant Colony Optimization (EBC_LEE-ACO) for Performance Enhancement of Wireless Sensor NetworkEngineering, Technology & Applied Science Research10.48084/etasr.21218:4(3177-3183)Online publication date: 18-Aug-2018
  • (2013)Using Ant Colony Agentsfor Designing Energy-Efficient Protocols for Wireless Ad Hoc and Sensor NetworksHandbook of Green Information and Communication Systems10.1016/B978-0-12-415844-3.00024-3(611-629)Online publication date: 2013
  • (2012)Towards Distributed Protocol Stacks for Wireless Sensor NetworksProceedings of the 2012 IEEE International Conference on Green Computing and Communications10.1109/GreenCom.2012.148(418-425)Online publication date: 20-Nov-2012

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