Article

An agent based approach to site selection for wireless networks

Authors:

Roger M. WhitakerAuthors Info & Claims

SAC '02: Proceedings of the 2002 ACM symposium on Applied computing

Pages 574 - 577

https://doi.org/10.1145/508791.508902

Published: 11 March 2002 Publication History

Abstract

The location of transmission infrastructure for wireless communication networks is an important engineering problem involving competing objectives. A minimal selection of locations (or sites) are required subject to providing adequate area coverage for users. In this paper we present a general model for this problem, related to circle packing and set covering. We show that the pattern matching algorithm known as stochastic diffusion search can be applied to identify suitable solutions even for large problem instances.

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Cited By

Baykasoğlu AÖzbel B(2021)Modeling and solving a real-world cutting stock problem in the marble industry via mathematical programming and stochastic diffusion search approachesComputers & Operations Research10.1016/j.cor.2020.105173128(105173)Online publication date: Apr-2021
https://doi.org/10.1016/j.cor.2020.105173
Legaspi JCanfield CGill KWyglinski ABhadai S(2020)Integrated Agent-Based Model for Broadband Resource Allocation Analysis2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)10.1109/VTC2020-Spring48590.2020.9129189(1-5)Online publication date: May-2020
https://doi.org/10.1109/VTC2020-Spring48590.2020.9129189
Tzanetos ADounias G(2020)A Comprehensive Survey on the Applications of Swarm Intelligence and Bio-Inspired Evolutionary StrategiesMachine Learning Paradigms10.1007/978-3-030-49724-8_15(337-378)Online publication date: 24-Jul-2020
https://doi.org/10.1007/978-3-030-49724-8_15
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An agent based approach to site selection for wireless networks

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Published In

cover image ACM Conferences

SAC '02: Proceedings of the 2002 ACM symposium on Applied computing

March 2002

1200 pages

ISBN:1581134452

DOI:10.1145/508791

Conference Chair:
Gary B. Lamont
Air Force Institute of Technology, USA
,
Program Chairs:
Hisham Haddad
Kennesaw State Univ., USA
,
George Papadopoulos
Univ. of Cyprus, Cyprus
,
Publications Chair:
Brajendra Panda
University of Arkansas, USA

Copyright © 2002 ACM.

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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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 March 2002

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SAC02: 2002 ACM Symposium on Applied Computing

March 11 - 14, 2002

Madrid, Spain

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Baykasoğlu AÖzbel B(2021)Modeling and solving a real-world cutting stock problem in the marble industry via mathematical programming and stochastic diffusion search approachesComputers & Operations Research10.1016/j.cor.2020.105173128(105173)Online publication date: Apr-2021
https://doi.org/10.1016/j.cor.2020.105173
Legaspi JCanfield CGill KWyglinski ABhadai S(2020)Integrated Agent-Based Model for Broadband Resource Allocation Analysis2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)10.1109/VTC2020-Spring48590.2020.9129189(1-5)Online publication date: May-2020
https://doi.org/10.1109/VTC2020-Spring48590.2020.9129189
Tzanetos ADounias G(2020)A Comprehensive Survey on the Applications of Swarm Intelligence and Bio-Inspired Evolutionary StrategiesMachine Learning Paradigms10.1007/978-3-030-49724-8_15(337-378)Online publication date: 24-Jul-2020
https://doi.org/10.1007/978-3-030-49724-8_15
JM B(2018)Recruiting robots perform stochastic diffusion searchInternational Robotics & Automation Journal10.15406/iratj.2018.04.001114:2Online publication date: 26-Apr-2018
https://doi.org/10.15406/iratj.2018.04.00111
Alhakbani Hal-Rifaie MBosman P(2017)Feature selection using stochastic diffusion searchProceedings of the Genetic and Evolutionary Computation Conference10.1145/3071178.3079193(385-392)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1145/3071178.3079193
Alhakbani Hal-Rifaie M(2016)A Swarm Intelligence Approach in Undersampling Majority ClassSwarm Intelligence10.1007/978-3-319-44427-7_19(225-232)Online publication date: 28-Aug-2016
https://doi.org/10.1007/978-3-319-44427-7_19
Wu NSilva E(2013)Selecting artificial intelligence urban models using waves of complexityProceedings of the Institution of Civil Engineers - Urban Design and Planning10.1680/udap.12.00014166:1(76-90)Online publication date: Feb-2013
https://doi.org/10.1680/udap.12.00014
al-Rifaie MBishop JBlackwell T(2012)Information sharing impact of stochastic diffusion search on differential evolution algorithmMemetic Computing10.1007/s12293-012-0094-y4:4(327-338)Online publication date: 9-Nov-2012
https://doi.org/10.1007/s12293-012-0094-y
al-Rifaie MBishop MBlackwell TLanzi P(2011)An investigation into the merger of stochastic diffusion search and particle swarm optimisationProceedings of the 13th annual conference on Genetic and evolutionary computation10.1145/2001576.2001583(37-44)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001576.2001583
Gibney AKlepal MPesch D(2011)Agent-Based Optimization for Large Scale WLAN DesignIEEE Transactions on Evolutionary Computation10.1109/TEVC.2010.206432415:4(470-486)Online publication date: 1-Aug-2011
https://dl.acm.org/doi/10.1109/TEVC.2010.2064324
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