Application execution management on the InteGrade opportunistic grid middleware
Journal of Parallel and Distributed Computing
Argumentation strategies for plan resourcing
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
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Autonomous Agents and Multi-Agent Systems
Argumentation strategies for collaborative plan resourcing
ArgMAS'11 Proceedings of the 8th international conference on Argumentation in Multi-Agent Systems
Scheduling highly available applications on cloud environments
Future Generation Computer Systems
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This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method's superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright © 2009 John Wiley & Sons, Ltd.