O domínio de grades computacionais é fortemente associado ao compartilhamento de recursos para a resolução de problemas em ambientes dinâmicos e heterogê- neos. Reutilizar aplicações armazenadas na grade e alocar recursos para atender os requisitos das aplicações são tarefas essenciais na grade e dependem da qualidade das informações disponíveis. O presente trabalho propõe uma abordagem semântica para a construção de um serviço de metadados sobre grades e sobre as aplicações nelas disponibilizadas. A abordagem proposta explora a realização de inferência sobre ontologias de aplicações e recursos computacionais da grade e a realização de consultas sobre a base inferida para promover a realização de tarefas, tais como escalonamento de recursos para execução de aplicações na grade, de modo e_ciente. O middleware para Grades oportunistas, InteGrade, foi a base a para o desenvolvimento desse projeto. / The grid computing domain is strongly related to resource sharing for problem resolution in dynamic and heterogeneous environments. The reuse of applications stored on grids and the allocation of resources to meet application requirements are essential grid tasks. These tasks depend on the quality of available information. This work proposes a semantic approach to build a metadata service about grid models, resources and applications. This approach explores inference and queries on ontologies about applications and grid computational resources aiming to enhance the execution of grid tasks, such as resource scheduling on grids. We used InteGrade, an opportunistic grid middleware, as the ground for the development of our project. The metadata integration will contribute to promote the e_cient usage of grid resources and applications.

O domínio de grades computacionais é fortemente associado ao compartilhamento de recursos para a resolução de problemas em ambientes dinâmicos e heterogê- neos. Reutilizar aplicações armazenadas na grade e alocar recursos para atender os requisitos das aplicações são tarefas essenciais na grade e dependem da qualidade das informações disponíveis. O presente trabalho propõe uma abordagem semântica para a construção de um serviço de metadados sobre grades e sobre as aplicações nelas disponibilizadas. A abordagem proposta explora a realização de inferência sobre ontologias de aplicações e recursos computacionais da grade e a realização de consultas sobre a base inferida para promover a realização de tarefas, tais como escalonamento de recursos para execução de aplicações na grade, de modo e_ciente. O middleware para Grades oportunistas, InteGrade, foi a base a para o desenvolvimento desse projeto. / The grid computing domain is strongly related to resource sharing for problem resolution in dynamic and heterogeneous environments. The reuse of applications stored on grids and the allocation of resources to meet application requirements are essential grid tasks. These tasks depend on the quality of available information. This work proposes a semantic approach to build a metadata service about grid models, resources and applications. This approach explores inference and queries on ontologies about applications and grid computational resources aiming to enhance the execution of grid tasks, such as resource scheduling on grids. We used InteGrade, an opportunistic grid middleware, as the ground for the development of our project. The metadata integration will contribute to promote the e_cient usage of grid resources and applications.

One of the fundamental requirements of Grid computing is efficient and effective resource discovery mechanism. Resource discovery involves discovery of appropriate resources required by user applications. In this regard various resource discovery mechanisms have been proposed during the recent years. These mechanisms range from centralized to hierarchical information servers approach. Most of the techniques developed based on these approaches have scalability and fault tolerance limitations. To overcome these limitations Peer to Peer based discovery mechanisms are proposed. / shairbaz@gmail.com

A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In the presence of grid users who are autonomous, rational, and intelligent, there is an overall degradation of the total efficiency of the computational grid in comparison to what can be achieved when the participating users are centrally coordinated . This loss in efficiency might arise due to an unwillingness on the part of some of the grid resource providers to either not perform completely or not perform to the fullest capability, the computational jobs of other users in the grid. In this thesis, our attention is focused on designing grid resource procurement mechanisms which a grid user can use for procuring resources in a computational grid based on bids submitted by autonomous, rational, and intelligent resource providers. Specifically, we follow a game theoretic and mechanism design approach to design three elegant, different incentive compatible procurement mechanisms for this purpose: G-DSIC (Grid-Dominant Strategy Incentive Compatible) mechanism which guarantees that truthful bidding is a best response for each resource provider, irrespective of what the other resource providers bid G-BIC (Grid-Bayesian Nash Incentive Compatible) mechanism which only guarantees that truthful bidding is a best response for each resource provider whenever all other resource providers also bid truthfully G-OPT (Grid-Optimal) mechanism which minimizes the cost to the grid user, satisfying at the same time, (1) Bayesian Incentive Compatibility (which guarantees that truthful bidding is a best response for each resource provider whenever all other resource providers also bid truthfully) and (2) Individual Rationality (which guarantees that the resource providers have non-negative payoffs if they participate in the bidding process). We evaluate the relative merits and demerits of the above three mechanisms using game theoretical analysis and numerical experiments. The mechanisms developed in this thesis are in the context of parameter sweep type of jobs, which consist of multiple homogeneous and independent tasks. We believe the use of the mechanisms proposed transcends beyond parameter sweep type of jobs and in general, the proposed mechanisms could be extended to provide a robust way of procuring resources in a computational grid where the resource providers exhibit rational and strategic behavior.