Improving the Performance of Fault-Aware Scheduling Policies for Desktop Grids (Be Lazy, Be Cool)

Abstract — Desktop Grids have proved to be a suitable platform for the execution of Bag-of-Tasks applications but, being characterized by a high resource volatility, require the availability of scheduling techniques able to effectively deal with resource failures and/or unplanned periods of unavailability. Fault-aware scheduling, proposed in [1], can be considered a promising approach, yielding to both performance improvements for Bagof-Task-Applications and increased utilization for Desktop Grids. The best fault-aware scheduling strategy available at the moment uses on-line scheduling, that is it starts a task as soon as a machine becomes available. In this paper we present a machine selection policy based on the idea that sometimes is better to wait for another machine rather than greedily exploit an immediately available one. An extensive simulation study, carried on for a variety of realistic Desktop Grid configurations and Bag-of-Task workloads, has revealed that the new scheduling strategy further improve application performance and machine utilization with respect to the best fault-aware scheduling strategy among those proposed in [1]. I

Workflow scheduling for service oriented cloud computing

Service Orientation (SO) and grid computing are two computing paradigms that when put together using Internet technologies promise to provide a scalable yet flexible computing platform for a diverse set of distributed computing applications. This practice gives rise to the notion of a computing cloud that addresses some previous limitations of interoperability, resource sharing and utilization within distributed computing. In such a Service Oriented Computing Cloud (SOCC), applications are formed by composing a set of services together. In addition, hierarchical service layers are also possible where general purpose services at lower layers are composed to deliver more domain specific services at the higher layer. In general an SOCC is a horizontally scalable computing platform that offers its resources as services in a standardized fashion. Workflow based applications are a suitable target for SOCC where workflow tasks are executed via service calls within the cloud. One or more workflows can be deployed over an SOCC and their execution requires scheduling of services to workflow tasks as the task become ready following their interdependencies. In this thesis heuristics based scheduling policies are evaluated for scheduling workflows over a collection of services offered by the SOCC. Various execution scenarios and workflow characteristics are considered to understand the implication of the heuristic based workflow scheduling