Exploiting Tuple Spaces to Provide Fault-Tolerant Scheduling on Computational Grids

Abstract

Scheduling tasks on large-scale computational grids is difficult due to the heterogeneous computational capabilities of the resources, node unavailability and unreliable network connectivity. This work proposes GRIDTS, a grid infrastructure in which the resources select the tasks they execute, instead of a scheduler finding resources for the tasks. This solution allows scheduling decisions to be made with up-to-date information about the resources. Moreover, GRIDTS provides fault-tolerant scheduling by combining a set of fault tolerance techniques to tolerate crash faults in components of the system. The core of the solution is a tuple space, which supports the communication, but also provides support for the fault tolerance mechanisms