Abstract
Abstract One main issue associated with the efficient and effective use of heterogeneous resources in a grid system is the scheduling. Scheduling in a grid system involves a number of challenging issues mainly due to the dynamic nature of the grid. Schedulers on traditional grid infrastructures rely on an information service that provides information about resources capacities and availability. However, in an asynchronous distributed system like a grid providing up-to-date information about resources is difficult. Current scheduling algorithms make scheduling decisions without fully accurate information about resources which can lead to inefficient schedules. This paper proposes a new scheduling infrastructure for grids where resources select tasks they execute, instead of the traditional approach where schedulers finding resources for the tasks. The new proposed approach allows, at any time, to make scheduling decisions with up-to-date/accurate information. Moreover, our infrastructure provides mechanisms to provide a fault tolerant scheduling. The proposed infrastructure is mainly based on the tuple space coordination model. In our evaluation study, a number of experiments with various simulation setting demonstrated the practicability of proposed infrastructure.
Highlights
Scheduling is an important issue in grid, computing systems
The scheduling task model provided by GRIDTS takes from broker the concern to know what resources the tasks will be executed
GRIDTS has the immediate benefit of not requiring an information service for indicating the resource utilization. It leverages naturally the scheduling completely decentralized and it enforces a natural form of load balancing since the resources pick tasks adequate to their conditions and get a new one whenever the previous ended
Summary
Grid scheduling requires a series of challenging tasks These include searching for resources in collections of geographically distributed heterogeneous computing systems and making scheduling decisions taking into consideration the quality of service. In GRIDTS, the resources select the tasks they want to execute, instead of the traditional infrastructure where schedulers find resources to execute the tasks. This solution does not use an information service and allows scheduling decisions to be done with up-to-date information, since naturally each resource has always up-to-date information about itself. It presents a new infrastructure for computational grids that allows resources to find tasks suited for their attributes, even if those attributes change with time. The infrastructure provides fault-tolerant scheduling by combining a set of traditional fault tolerance techniques to tolerate crash faults in any component of its infrastructure
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