Cluster formation based on improved many optimizing liaisons optimization algorithm in wireless sensor networks

Zhiyong Li; Esraa Mohammed; Ahmed M. Ali; Gbadebo Joshua Adebayo; Lv Huang

doi:10.4156/ijact.vol3.issue5.29

Cluster formation based on improved many optimizing liaisons optimization algorithm in wireless sensor networks

Zhiyong Li, Esraa Mohammed, Ahmed M. Ali, Gbadebo Joshua Adebayo, Lv Huang

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

Extending Wireless Sensor Networks (WSNs) lifetime is one prominent challenge nowadays. Clustering in WSNs is used to manage energy consumption through data aggregation at the cluster head. WSNs energy-aware clustering is often formulated as an optimization problem. Therefore, an Improved Swarm Intelligence algorithm is proposed, named Improved Many Optimizing Liaisons (IMOL). The proposed algorithm is proposed to optimize the wireless sensor clustering to extend the network lifetime. This paper presents different comparisons among IMOL and the famous heuristic clustering algorithms. Simulation results demonstrate that the proposed IMOL algorithm gave a higher network lifetime over its comparatives.

Original language	English
Pages (from-to)	249-256
Number of pages	8
Journal	International Journal of Advancements in Computing Technology
Volume	3
Issue number	5
DOIs	https://doi.org/10.4156/ijact.vol3.issue5.29
State	Published - Jun 2011
Externally published	Yes

Keywords

Clustering algorithms
Swarm intelligence algorithms
Wireless sensor networks

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10.4156/ijact.vol3.issue5.29

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title = "Cluster formation based on improved many optimizing liaisons optimization algorithm in wireless sensor networks",

abstract = "Extending Wireless Sensor Networks (WSNs) lifetime is one prominent challenge nowadays. Clustering in WSNs is used to manage energy consumption through data aggregation at the cluster head. WSNs energy-aware clustering is often formulated as an optimization problem. Therefore, an Improved Swarm Intelligence algorithm is proposed, named Improved Many Optimizing Liaisons (IMOL). The proposed algorithm is proposed to optimize the wireless sensor clustering to extend the network lifetime. This paper presents different comparisons among IMOL and the famous heuristic clustering algorithms. Simulation results demonstrate that the proposed IMOL algorithm gave a higher network lifetime over its comparatives.",

keywords = "Clustering algorithms, Swarm intelligence algorithms, Wireless sensor networks",

author = "Zhiyong Li and Esraa Mohammed and Ali, \{Ahmed M.\} and Adebayo, \{Gbadebo Joshua\} and Lv Huang",

year = "2011",

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doi = "10.4156/ijact.vol3.issue5.29",

language = "English",

volume = "3",

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AU - Li, Zhiyong

AU - Mohammed, Esraa

AU - Ali, Ahmed M.

AU - Adebayo, Gbadebo Joshua

AU - Huang, Lv

PY - 2011/6

Y1 - 2011/6

N2 - Extending Wireless Sensor Networks (WSNs) lifetime is one prominent challenge nowadays. Clustering in WSNs is used to manage energy consumption through data aggregation at the cluster head. WSNs energy-aware clustering is often formulated as an optimization problem. Therefore, an Improved Swarm Intelligence algorithm is proposed, named Improved Many Optimizing Liaisons (IMOL). The proposed algorithm is proposed to optimize the wireless sensor clustering to extend the network lifetime. This paper presents different comparisons among IMOL and the famous heuristic clustering algorithms. Simulation results demonstrate that the proposed IMOL algorithm gave a higher network lifetime over its comparatives.

AB - Extending Wireless Sensor Networks (WSNs) lifetime is one prominent challenge nowadays. Clustering in WSNs is used to manage energy consumption through data aggregation at the cluster head. WSNs energy-aware clustering is often formulated as an optimization problem. Therefore, an Improved Swarm Intelligence algorithm is proposed, named Improved Many Optimizing Liaisons (IMOL). The proposed algorithm is proposed to optimize the wireless sensor clustering to extend the network lifetime. This paper presents different comparisons among IMOL and the famous heuristic clustering algorithms. Simulation results demonstrate that the proposed IMOL algorithm gave a higher network lifetime over its comparatives.

KW - Clustering algorithms

KW - Swarm intelligence algorithms

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EP - 256

JO - International Journal of Advancements in Computing Technology

JF - International Journal of Advancements in Computing Technology

IS - 5

ER -

Cluster formation based on improved many optimizing liaisons optimization algorithm in wireless sensor networks

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Keywords

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