Fault tolerance in computational grids: perspectives, challenges, and issues

Abstract

Computational grids are established with the intention of providing shared access to hardware and software based resources with special reference to increased computational capabilities. Fault tolerance is one of the most important issues faced by the computational grids. The main contribution of this survey is the creation of an extended classification of problems that incur in the computational grid environments. The proposed classification will help researchers, developers, and maintainers of grids to understand the types of issues to be anticipated. Moreover, different types of problems, such as omission, interaction, and timing related have been identified that need to be handled on various layers of the computational grid. In this survey, an analysis and examination is also performed pertaining to the fault tolerance and fault detection mechanisms. Our conclusion is that a dependable and reliable grid can only be established when more emphasis is on fault identification. Moreover, our survey reveals that adaptive and intelligent fault identification, and tolerance techniques can improve the dependability of grid working environments.

DBRS: Directed Acyclic Graph based Reliable Scheduling Approach in Large Scale Computing

“…Computing on a grid can be useful in a wide variety of contexts, including the fields of medicine, meteorology, engineering, and research, amongst others. When it comes to research, the most important aspects of grid computing are task scheduling and ensuring fault tolerance [3].…”

Designing and Implementation of Failure-Aware Based Approach for Task Scheduling in Grid Computing

“…Failures can make a process run slower than normal or even stop it. A resource/node failure can be caused by failure of any of the component in Grid which may be a processor, memory, network connection and application/software [21]. Thus, failure information, in addition to other performance-related factors, should be taken into account when making scheduling decisions.…”