Resource use pattern analysis for opportunistic grids

Abstract

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. The basic assumptions of the method and its capability to predict resource availability were demonstrated by simulations; accurate learning techniques and distance metrics are determined. The UPA method was implemented and experiments showed the feasibility of its use in low-overhead scheduling of grid tasks and its superiority over other predictive and non-predictive methods.