The resource availability in Grids is generally unpredictable due to the autonomous and shared nature of the Grid resources and stochastic nature of the workload resulting in a best effort quality of service. The resource providers optimize for throughput and utilization whereas the users optimize for application performance. We present a cost-based model where the providers advertise resource availability to the user community. We also present a multi-objective genetic algorithm formulation for selecting the set of resources to be provisioned that optimizes the application performance while minimizing the resource costs. We use trace-based simulations to compare the application performance and cost using the provisioned and the best effort approach with a number of artificially generated workflow-structured applications and a seismic hazard application from the earthquake science community. The provisioned approach shows promising results when the resources are under high utilization and/or the applications have significant resource requirements.

In this paper we present an extension to devise and implement advance reservation as part of the scheduling and resource management services of the ASKALON Grid application development and runtime environment. The scheduling service has been enhanced to offer a list of resources that can execute a specific task and to negotiate with the resource manager about resources capable of processing tasks in the shortest possible time. We introduce progressive reservation approach which tries to allocate resources based on a fair-share principle. Experiments are shown that demonstrate the effectiveness of our approach, and that reflect different QoS parameters including performance, predictability, resource usage and resource fairness. 2

Abstract. Emerging deadline-driven Grid applications require a number of computing resources to be available over a time frame, starting at a specific time in the future. To enable these applications, it is important to predict the resource availability and utilise this information during provisioning because it affects their performance. It is impractical to request the availability information upon the scheduling of every job due to communication overhead. However, existing work has not considered how the precision of availability information influences the provisioning. As a result, limitations exist in developing advanced resource provisioning and scheduling mechanisms. This work investigates how the precision of availability information affects resource provisioning in multiple site environments. Performance evaluation is conducted considering both multiple scheduling policies in resource providers and multiple provisioning policies in brokers, while varying the precision of availability information. Experimental results show that it is possible to avoid requesting availability information for every Grid job scheduled thus reducing the communication overhead. They also demonstrate that multiple resource partition policies improve the slowdown of Grid jobs. 1

playsakeyroleinGridresourcemanagementasitenables thesystemtomeetuserexpectationswithrespecttotime requirements and temporal dependence of applications, increases predictability of the system and enables coallocation of resources. Despite these attractive features, adoptionofadvancereservationsislimitedmainlydueto thefactthatrelatedalgorithmsaretypicallycomplexand fail to scale to large and loaded systems. In this work weconsidertwoaspectsofadvancereservations.First,we investigatetheimpactofheterogeneityonGridresource management when advance reservations are supported. Second,weemploytechniquesfromcomputationalgeometrytodevelopanefficientheterogeneity-awarescheduling algorithm.OurmainfindingisthatGridsmaybenefitfrom highlevelsofresourceheterogeneity,independentlyofthe totalsystemcapacity.Ourresultsshowthatouralgorithm performswellacrossseveraluserandsystemperformance andovercomethelackofscalabilityandadaptabilityof existingmechanisms. I.

Several Grids have been established and used for varying science applications during the last years. Most of these Grids, however, work in isolation and with different utilisation levels. Previous work introduced an architecture and a mechanism to enable resource sharing amongst Grids. It demonstrated that there can be benefits for a Grid to offload requests or provide spare resources to another Grid, thus reducing the cost of over-provisioning. These benefits derive from the fact that resource utilisation within a Grid has fixed and operational costs such as those with electricity providers and system administrators. In this work, we address the problem of resource provisioning to Grid applications in multiple-Grid environments. The provisioning is carried out based on availability information obtained from queueing-based resource management systems deployed at the provider sites who are the participants of the Grids. We evaluate the performance of different allocation policies. In contrast to existing work on load sharing across Grids, the policies described here take into account the local load of resource providers, imprecise availability information and the monetary compensation of providers. In addition, we evaluate these policies along with mechanism that allows resource sharing amongst Grids. Experimental results obtained through simulation show that the mechanism and policies are effective in redirecting requests thus improving the applications’ average weighted response time.