Swarm optimisation algorithms applied to large balanced communication networks

  • Authors:

  • EugéNia Moreira Bernardino;Anabela Moreira Bernardino;Juan Manuel SáNchez-PéRez;Juan Antonio GóMez Pulido;Miguel A. Vega RodríGuez

  • Affiliations:

  • Computer Science and Communication Research Centre, Dept. of Computer Science, School of Technology and Management, Polytechnic Institute of Leiria, Leiria, Portugal;Computer Science and Communication Research Centre, Dept. of Computer Science, School of Technology and Management, Polytechnic Institute of Leiria, Leiria, Portugal;Dept. of Technologies of Computers and Communications, Polytechnic School, University of Extremadura, Cáceres, Spain;Dept. of Technologies of Computers and Communications, Polytechnic School, University of Extremadura, Cáceres, Spain;Dept. of Technologies of Computers and Communications, Polytechnic School, University of Extremadura, Cáceres, Spain

  • Venue:
  • Journal of Network and Computer Applications
  • Year:
  • 2013

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Abstract

In the last years, several combinatorial optimisation problems have arisen in the computer communications networking field. In many cases, for solving these problems it is necessary the use of meta-heuristics. An important problem in communication networks is the Terminal Assignment Problem (TAP). Our goal is to minimise the link cost of large balanced communication networks. TAP is a NP-Hard problem. The intractability of this problem is the motivation for the pursuits of Swarm Intelligence (SI) algorithms that produce approximate, rather than exact, solutions. This paper makes a comparison among the effectiveness of three SI algorithms: Ant Colony Optimisation, Discrete Particle Swarm Optimisation and Artificial Bee Colony. We also compare the SI algorithms with several algorithms from literature. Simulation results verify the effectiveness of the proposed algorithms. The results show that SI algorithms provide good solutions in a better running time.