Clustered Computing with NetLogo for the evaluation of asynchronous search techniques

Abstract

Distributed Constraint programming is a programming approach used to describe and solve large classes of problems such as searching, combinatorial and planning problems. A Distributed Constraint Satisfaction is a constraint satisfaction problem in which variables and constraints are distributed among multiple agents. Modelling and simulation are essential tools in many areas of science and engineering, including computer science. The purpose of this article is to present an open-source tools in NetLogo for implementation and evaluation of the asynchronous searching techniques for a great number of agents, tool that can be run on a cluster of computers. Also, in this paper we have developed a methodology to run the NetLogo models in a cluster computing environment or on a single machine, varying both parameter values and/or random number of agents. Such a tool allows using various search techniques also the evaluation and analysis of performances of the techniques for the asynchronous searching techniques, the study of agents behaviour in several situations, like the priority order of the agents, the synchronous and asynchronous case, apparition of delays in message transmission, leading, therefore, to identifying possible enhancements of the performances of asynchronous search techniques.