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Computers 2015, 4(1), 2-23; doi:10.3390/computers4010002

A Hybrid Autonomic Computing-Based Approach to Distributed Constraint Satisfaction Problems

University School of Information and Communication Technology (USICT), GGS IndraprasthaUniversity, Sector 16C Dwarka, New Delhi 110078, India
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Academic Editor: Aaron Quigley
Received: 14 October 2014 / Revised: 12 January 2015 / Accepted: 3 March 2015 / Published: 13 March 2015
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Abstract

Distributed constraint satisfaction problems (DisCSPs) are among the widely endeavored problems using agent-based simulation. Fernandez et al. formulated sensor and mobile tracking problem as a DisCSP, known as SensorDCSP In this paper, we adopt a customized ERE (environment, reactive rules and entities) algorithm for the SensorDCSP, which is otherwise proven as a computationally intractable problem. An amalgamation of the autonomy-oriented computing (AOC)-based algorithm (ERE) and genetic algorithm (GA) provides an early solution of the modeled DisCSP. Incorporation of GA into ERE facilitates auto-tuning of the simulation parameters, thereby leading to an early solution of constraint satisfaction. This study further contributes towards a model, built up in the NetLogo simulation environment, to infer the efficacy of the proposed approach. View Full-Text
Keywords: distributed constraint satisfaction problems; autonomic computing; agent-based simulation; genetic algorithm; NetLogo distributed constraint satisfaction problems; autonomic computing; agent-based simulation; genetic algorithm; NetLogo
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Bhatia, A.; Singh, A.; Goyal, R. A Hybrid Autonomic Computing-Based Approach to Distributed Constraint Satisfaction Problems. Computers 2015, 4, 2-23.

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