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Issue title: Recent advancements in computer, communication and computational sciences
Guest editors: K.K. Mishra
Article type: Research Article
Authors: Punhani, Akasha; * | Kumar, Pardeepa | Nitin, b
Affiliations: [a] Department of Computer Science and Engineering, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India | [b] Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India
Correspondence: [*] Corresponding author. Akash Punhani, Department of Computer Science and Engineering, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India. Tel.: +91 8006642369 Fax: +91 1792 245362; E-mail: akashpunhani@gmail.com.
Abstract: Many variants of the mesh interconnection networks have been suggested in past by the placement of the extra links to the existing mesh topology. In this paper, we have searched for the optimal links that should place in the topology so as to reduce the average inter node distance of the resultant topology. This is a heuristic search problem which has the single objective that is to minimize the average inter node distance of the topology. The Improved Environmental Adaptation Method (IEAM) is one of the latest techniques based on phenotypic properties of genes, which prove to be fast in searching the optimal solution to the problem. The paper describes in detail the various operator of IEAM and compares its performance with the existing heuristic technique that is Genetic algorithm. The IEAM obviously proves to be better in finding the results. After finding the optimized topology the resultant is tested for the performance with existing variant of the topology like mesh, center concentrated mesh, T Mesh for performance and proves to give the improvement more than 2 times.
Keywords: Optimization, environmental adaptation method, interconnection network, average inter node distance, performance evaluation
DOI: 10.3233/JIFS-169271
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3285-3295, 2017
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