Swarm Intelligence Approach for Ad-Hoc Networks

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Author(s): Prayag Narula (University of Delhi, India), Sudip Misra (Yale University, USA)and Sanjay Kumar Dhurandher (University of Delhi, India)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Artificial Intelligence
Source Author(s)/Editor(s): Juan Ramón Rabuñal Dopico (University of A Coruña, Spain), Julian Dorado (University of A Coruña, Spain)and Alejandro Pazos (University of A Coruña, Spain)
DOI: 10.4018/978-1-59904-849-9.ch224

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

Wireless ad-hoc networks are infrastructureless and they consist of nodes that come together and start communicating dynamically without requiring any backbone support. The nodes can enter and leave the network at will and can move about in the network at will. Ad-hoc networks present the perfect test-beds for bio-inspired computing algorithms. Both ad-hoc networks and bio-inspired computing approaches are characterized by self-organization, feedback and structural and functional complexity (Toh, 2002) (deCastro & Von Zuben, 2005). Hence, bio-inspired algorithms often provide us an opportunity to solve the most complex problems of ad-hoc networks in a satisfactory manner. In this chapter, we present the works done in the field of ad-hoc networks using bio-inspired Swarm Intelligence (SI). In particular, we look at how we can use Ant Colony Optimization (ACO) technique, a SI technique, for optimal routing in ad-hoc networks.

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