Model for Anticipating Frank Failures in Computing Grids

Abstract

Computing grids are infrastructures that provide almost infinite computing capacities, they are now used in all fields, from the study of pandemics to the monitoring of rocket trajectories and the study of meteorological and climatic phenomena. They have a distributed and heterogeneous architecture that gives them unlimited computing performance. They are made up of several computing nodes that are subject to failures like frank failures. A frank failure in a computing grid is an abnormal and unexpected interruption of a node. Many frank failure tolerance protocols have been proposed in the literature but none of these protocols integrate the anticipation of frank failures. The objective of this article is to propose a model based on the PDEVS formalism of frank failure tolerance in a computing grid that allows the anticipation of frank failures. The proposed model relies on the temperature variation of electronic components and on the state of the hard disk through the values provided by SMART data to predict a probable frank failure of a node. The results of the simulations on the different scenarios that we have carried out show that our results provide better performances than those proposed in the literature when the number of nodes to tolerate is greater than 200.