An improved particle swarm optimization algorithm for power-efficient wireless sensor networks

Erfu Yang; Ahmet T. Erdogan; Tughrul Arslan; Nick Barton

doi:10.1109/BLISS.2007.19

An improved particle swarm optimization algorithm for power-efficient wireless sensor networks

Erfu Yang, Ahmet T. Erdogan, Tughrul Arslan, Nick Barton

Design, Manufacturing And Engineering Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

15 Citations (Scopus)

Abstract

This paper presents an improved particle swarm optimization (PSO) algorithm for onboard embedded applications in power-efficient wireless sensor networks (WSNs) and WSN-based security systems. The objective is to keep the main advantages of the standard PSO algorithm, such as simple form, easy implementation, low algorithmic complexity, and low computational burden while the performance and efficiency can be significantly improved. Numerical experiments are performed on a very difficult benchmark function to validate the performance of the improved PSO algorithm. The results show that the improved PSO algorithm outperforms the standard PSO algorithm.

Original language	English
Title of host publication	ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007
Editors	Adrian Stoica, Tughrul Arslan, Daniel Howard, Tai-Hoon Kim, Ahmed El-Rayis
Place of Publication	Los Alamitos, CA.
Pages	76-79
Number of pages	4
DOIs	https://doi.org/10.1109/BLISS.2007.19
Publication status	Published - 29 Jan 2008
Event	2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007 - Edinburgh, United Kingdom Duration: 9 Aug 2007 → 10 Aug 2007

Conference

Conference	2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007
Country/Territory	United Kingdom
City	Edinburgh
Period	9/08/07 → 10/08/07

Keywords

particle swarm optimisation
telecommunication security
wireless sensor networks
evolutionary computation
intelligent networks
intelligent sensors
monitoring
power engineering and energy
power system security
sensor systems
system-on-a-chip

Access to Document

10.1109/BLISS.2007.19

Cite this

Yang, E., Erdogan, A. T., Arslan, T., & Barton, N. (2008). An improved particle swarm optimization algorithm for power-efficient wireless sensor networks. In A. Stoica, T. Arslan, D. Howard, T-H. Kim, & A. El-Rayis (Eds.), ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007 (pp. 76-79). [4290943]. https://doi.org/10.1109/BLISS.2007.19

Yang, Erfu ; Erdogan, Ahmet T. ; Arslan, Tughrul ; Barton, Nick. / An improved particle swarm optimization algorithm for power-efficient wireless sensor networks. ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007. editor / Adrian Stoica ; Tughrul Arslan ; Daniel Howard ; Tai-Hoon Kim ; Ahmed El-Rayis. Los Alamitos, CA., 2008. pp. 76-79

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abstract = "This paper presents an improved particle swarm optimization (PSO) algorithm for onboard embedded applications in power-efficient wireless sensor networks (WSNs) and WSN-based security systems. The objective is to keep the main advantages of the standard PSO algorithm, such as simple form, easy implementation, low algorithmic complexity, and low computational burden while the performance and efficiency can be significantly improved. Numerical experiments are performed on a very difficult benchmark function to validate the performance of the improved PSO algorithm. The results show that the improved PSO algorithm outperforms the standard PSO algorithm.",

keywords = "particle swarm optimisation, telecommunication security, wireless sensor networks, evolutionary computation, intelligent networks, intelligent sensors, monitoring, power engineering and energy, power system security, sensor systems, system-on-a-chip",

author = "Erfu Yang and Erdogan, {Ahmet T.} and Tughrul Arslan and Nick Barton",

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booktitle = "ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007",

note = "2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007 ; Conference date: 09-08-2007 Through 10-08-2007",

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Yang, E, Erdogan, AT, Arslan, T & Barton, N 2008, An improved particle swarm optimization algorithm for power-efficient wireless sensor networks. in A Stoica, T Arslan, D Howard, T-H Kim & A El-Rayis (eds), ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007., 4290943, Los Alamitos, CA., pp. 76-79, 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2007, Edinburgh, United Kingdom, 9/08/07. https://doi.org/10.1109/BLISS.2007.19

An improved particle swarm optimization algorithm for power-efficient wireless sensor networks. / Yang, Erfu; Erdogan, Ahmet T.; Arslan, Tughrul; Barton, Nick.

ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007. ed. / Adrian Stoica; Tughrul Arslan; Daniel Howard; Tai-Hoon Kim; Ahmed El-Rayis. Los Alamitos, CA., 2008. p. 76-79 4290943.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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AU - Erdogan, Ahmet T.

AU - Arslan, Tughrul

AU - Barton, Nick

PY - 2008/1/29

Y1 - 2008/1/29

N2 - This paper presents an improved particle swarm optimization (PSO) algorithm for onboard embedded applications in power-efficient wireless sensor networks (WSNs) and WSN-based security systems. The objective is to keep the main advantages of the standard PSO algorithm, such as simple form, easy implementation, low algorithmic complexity, and low computational burden while the performance and efficiency can be significantly improved. Numerical experiments are performed on a very difficult benchmark function to validate the performance of the improved PSO algorithm. The results show that the improved PSO algorithm outperforms the standard PSO algorithm.

AB - This paper presents an improved particle swarm optimization (PSO) algorithm for onboard embedded applications in power-efficient wireless sensor networks (WSNs) and WSN-based security systems. The objective is to keep the main advantages of the standard PSO algorithm, such as simple form, easy implementation, low algorithmic complexity, and low computational burden while the performance and efficiency can be significantly improved. Numerical experiments are performed on a very difficult benchmark function to validate the performance of the improved PSO algorithm. The results show that the improved PSO algorithm outperforms the standard PSO algorithm.

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KW - telecommunication security

KW - wireless sensor networks

KW - evolutionary computation

KW - intelligent networks

KW - intelligent sensors

KW - monitoring

KW - power engineering and energy

KW - power system security

KW - sensor systems

KW - system-on-a-chip

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Yang E, Erdogan AT, Arslan T, Barton N. An improved particle swarm optimization algorithm for power-efficient wireless sensor networks. In Stoica A, Arslan T, Howard D, Kim T-H, El-Rayis A, editors, ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, 2007. BLISS 2007. Los Alamitos, CA. 2008. p. 76-79. 4290943 https://doi.org/10.1109/BLISS.2007.19

An improved particle swarm optimization algorithm for power-efficient wireless sensor networks

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Keywords

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