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

Uma heuristica de agrupamento de caminhos para escalonamento de tarefas em grades computacionais

Orientador: Edmundo Roberto Mauro MadeiraDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Uma grade computacional é um sistema heterogêneo colaborativo, geograficamente distribuído, multi-institucional e dinâmico, onde qualquer recurso computacional ligado a uma rede, local ou não, é um potencial colaborador. Grades computacionais são atualmente um grande foco de estudos relacionados à execução de aplicações paralelas, tanto aquelas que demandam grande poder computacional quanto aquelas que se adaptam bem a ambientes distribuídos. Como os recursos de uma grade pertencem a vários domínios administrativos diferentes com políticas diferentes, cada recurso tem autonomia para participar ou deixar de participar da grade em qualquer momento. Essa característica dinâmica e a heterogeneidade tornam o escalonamento de aplicações, a gerência de recursos e a tolerância a falhas grandes desafios nesses sistemas. Particularmente, o escalonamento desempenha um papel de suma importância, pois é determinante no tempo de execução das aplicações. O escalonamento de tarefas é um problema NP-Completo [6], o que levou ao desenvolvimento de uma heurística para o problema de otimização associado. Neste trabalho apresentamos um escalonador de tarefas em grades computacionais baseado no Xavantes [3], um middleware que oferece suporte a execução de tarefas dependentes através de estruturas de controle hierárquicas chamadas controladores. O algoritmo desenvolvido, chamado de Path Clustering Heuristic (PCH), agrupa as tarefas com o objetivo de minimizar a comunicação entre os controladores e as tarefas, diminuindo o tempo de execução total do processoAbstract: A computational grid is a collaborative heterogeneous, geographically distributed, multiinstitutional and dynamic system, where any computational resource with a network connection, local or remote, is a potential collaborator. In computational grids, problems related to the execution of parallel applications, those which need a lot of computational power, as well as those which fit well in distributed environments, are wide studied nowadays. As the grid resources belong to various different administrative domains with different policies, each resource has the autonomy to participate or leave the grid at any time. These dynamic and heterogeneous characteristics make the application scheduling, the resource management and the fault tolerance relevant issues on these systems. Particularly, the scheduler plays an important role, since it is determinative in the execution time of an application. The task scheduling problem is NP-Complete [6], what led to the development of a heuristic for the associated optimization problem. In this work we present a task scheduler for a computational grid based on Xavantes [3], a middleware that supports dependent task execution through control structures called controllers. The developed algorithm, called Path Clustering Heuristic (PCH), clusterizes tasks aiming to minimize the communication between controllers and tasks, reducing the process execution timeMestradoSistemas de ComputaçãoMestre em Ciência da Computaçã