Ant Colony Algorithms for Steiner Trees: An Application to Routing in Sensor Networks

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Author(s): Gurdip Singh (Kansas State University, USA), Sanjoy Das (Kansas State University, USA), Shekhar V. Gosavi (Kansas State University, USA)and Sandeep Pujar (Kansas State University, USA)
Copyright: 2005
Pages: 26
Source title: Recent Developments in Biologically Inspired Computing
Source Author(s)/Editor(s): Leandro Nunes de Castro (Mackenzie University, Brazil)and Fernando J. Von Zuben (State University of Campinas, Brazil)
DOI: 10.4018/978-1-59140-312-8.ch008

Keywords: Bioinformatics / Biologically-Inspired Computing / Medical Information Science Reference / Medicine & Healthcare

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Abstract

This chapter introduces ant colony optimization as a method for computing minimum Steiner trees in graphs. Tree computation is achieved when multiple ants, starting out from different nodes in the graph, move towards one another and ultimately merge into a single entity. A distributed version of the proposed algorithm is also described, which is applied to the specific problem of data-centric routing in wireless sensor networks. This research illustrates how tree based graph theoretic computations can be accomplished by means of purely local ant interaction. The authors hope that this work will demonstrate how innovative ways to carry out ant interactions can be used to design effective ant colony algorithms for complex optimization problems.

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Ant Colony Algorithms for Steiner Trees: An Application to Routing in Sensor Networks

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