An Artificial Fish Swarm Algorithm for the Multicast Routing Problem

Qing LIU; Tomohiro ODAKA; Jousuke KUROIWA; Haruhiko SHIRAI; Hisakazu OGURA

doi:10.1587/transcom.E97.B.996

An Artificial Fish Swarm Algorithm for the Multicast Routing Problem

Qing LIU, Tomohiro ODAKA, Jousuke KUROIWA, Haruhiko SHIRAI, Hisakazu OGURA

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This paper presents an artificial fish swarm algorithm (AFSA) to solve the multicast routing problem, which is abstracted as a Steiner tree problem in graphs. AFSA adopts a 0-1 encoding scheme to represent the artificial fish (AF), which are then subgraphs in the original graph. For evaluating each AF individual, we decode the subgraph into a Steiner tree. Based on the adopted representation of the AF, we design three AF behaviors: randomly moving, preying, and following. These behaviors are organized by a strategy that guides AF individuals to perform certain behaviors according to certain conditions and circumstances. In order to investigate the performance of our algorithm, we implement exhaustive simulation experiments. The results from the experiments indicate that the proposed algorithm outperforms other intelligence algorithms and can obtain the least-cost multicast routing tree in most cases.

Publication: IEICE TRANSACTIONS on Communications Vol.E97-B No.5 pp.996-1011

Publication Date: 2014/05/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E97.B.996

Type of Manuscript: PAPER

Category: Network

Authors

Qing LIU
  University of Fukui
Tomohiro ODAKA
  University of Fukui
Jousuke KUROIWA
  University of Fukui
Haruhiko SHIRAI
  University of Fukui
Hisakazu OGURA
  University of Fukui

Keyword

artificial fish swarm algorithm, multicast routing, Steiner tree problem, network optimization

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Qing LIU, Tomohiro ODAKA, Jousuke KUROIWA, Haruhiko SHIRAI, Hisakazu OGURA, "An Artificial Fish Swarm Algorithm for the Multicast Routing Problem" in IEICE TRANSACTIONS on Communications, vol. E97-B, no. 5, pp. 996-1011, May 2014, doi: 10.1587/transcom.E97.B.996.
Abstract: This paper presents an artificial fish swarm algorithm (AFSA) to solve the multicast routing problem, which is abstracted as a Steiner tree problem in graphs. AFSA adopts a 0-1 encoding scheme to represent the artificial fish (AF), which are then subgraphs in the original graph. For evaluating each AF individual, we decode the subgraph into a Steiner tree. Based on the adopted representation of the AF, we design three AF behaviors: randomly moving, preying, and following. These behaviors are organized by a strategy that guides AF individuals to perform certain behaviors according to certain conditions and circumstances. In order to investigate the performance of our algorithm, we implement exhaustive simulation experiments. The results from the experiments indicate that the proposed algorithm outperforms other intelligence algorithms and can obtain the least-cost multicast routing tree in most cases.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E97.B.996/_p

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@ARTICLE{e97-b_5_996,
author={Qing LIU, Tomohiro ODAKA, Jousuke KUROIWA, Haruhiko SHIRAI, Hisakazu OGURA, },
journal={IEICE TRANSACTIONS on Communications},
title={An Artificial Fish Swarm Algorithm for the Multicast Routing Problem},
year={2014},
volume={E97-B},
number={5},
pages={996-1011},
abstract={This paper presents an artificial fish swarm algorithm (AFSA) to solve the multicast routing problem, which is abstracted as a Steiner tree problem in graphs. AFSA adopts a 0-1 encoding scheme to represent the artificial fish (AF), which are then subgraphs in the original graph. For evaluating each AF individual, we decode the subgraph into a Steiner tree. Based on the adopted representation of the AF, we design three AF behaviors: randomly moving, preying, and following. These behaviors are organized by a strategy that guides AF individuals to perform certain behaviors according to certain conditions and circumstances. In order to investigate the performance of our algorithm, we implement exhaustive simulation experiments. The results from the experiments indicate that the proposed algorithm outperforms other intelligence algorithms and can obtain the least-cost multicast routing tree in most cases.},
keywords={},
doi={10.1587/transcom.E97.B.996},
ISSN={1745-1345},
month={May},}

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TY - JOUR
TI - An Artificial Fish Swarm Algorithm for the Multicast Routing Problem
T2 - IEICE TRANSACTIONS on Communications
SP - 996
EP - 1011
AU - Qing LIU
AU - Tomohiro ODAKA
AU - Jousuke KUROIWA
AU - Haruhiko SHIRAI
AU - Hisakazu OGURA
PY - 2014
DO - 10.1587/transcom.E97.B.996
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E97-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2014
AB - This paper presents an artificial fish swarm algorithm (AFSA) to solve the multicast routing problem, which is abstracted as a Steiner tree problem in graphs. AFSA adopts a 0-1 encoding scheme to represent the artificial fish (AF), which are then subgraphs in the original graph. For evaluating each AF individual, we decode the subgraph into a Steiner tree. Based on the adopted representation of the AF, we design three AF behaviors: randomly moving, preying, and following. These behaviors are organized by a strategy that guides AF individuals to perform certain behaviors according to certain conditions and circumstances. In order to investigate the performance of our algorithm, we implement exhaustive simulation experiments. The results from the experiments indicate that the proposed algorithm outperforms other intelligence algorithms and can obtain the least-cost multicast routing tree in most cases.
ER -