Modelling of a self-led critical friend topology in inter-cooperative grid communities (original) (raw)
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Tremendous advancement and more readily availability of Grid technologies encourages organizations to establish in-house Grids and make use of their available desktop resources to solve computing intensive problems. These mini Grids, because of their limited scope and resource availability, may not serve the real world problem in every aspect and, hence, lead them to collaborate on demand with other grids while keeping themselves autonomous and independent. The specific problem that underlies in such collaborative Grids is resource scheduling among autonomously administrated Grids. In this paper*, we propose a distributed, scalable and reconfigurable inter-Grid resource sharing framework where Grids can dynamically join or resign the framework on a need base. This framework, based on peer-to-peer communication paradigm, enables resource sharing among autonomous Grid systems.
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Much work has been done to exploit the effectiveness and efficiency of job scheduling upon distributed computational resources. With regard to existing resource topology and administrative constraints, scheduling approaches are designed for different hierarchic layers, for example, scheduling for job queues of local resource management systems (local scheduling), and scheduling for job queues of high level schedulers (also known as meta-schedulers or grid schedulers). Such scheduling approaches mainly focus on optimizing job queues of the hosting nodes, which are interconnected with computational resources directly or indirectly. In the real world (or in a community-based grid), a grid is comprised of nodes with different computing power and scheduling preferences, which in turn, raise a notable opportunity that is to exploit and optimize the process of job sharing between reachable grid nodes via improving the job allocation and efficiency ratio.
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The access to Grid resources depends on policies defined by the administrators of the physical organizations and of the Grid middleware. This approach does not require support for access control in the middleware, but since changes in the access control policy of the Virtual Organization imply the involvement of one or more administrators, it lacks the flexibility needed in several application scenarios. In this paper we propose a group-based access control model for Grid environments that increases the flexibility of the access control model offered by state-of-the-art Grid platforms without requiring changes in the middleware. The approach is based on collaboration among Grid users and allows them to exchange access permissions to Virtual Resources without the intervention of administrators. We show that our solution can be defined on top of the access control mechanisms offered by state-of-the-art Grid middleware and illustrate how the proposed model can be implemented as a servi...
The Journal of Supercomputing, 2008
Rapid advancement and more readily availability of Grid technologies have encouraged many businesses and researchers to establish Virtual Organizations (VO) and make use of their available desktop resources to solve computing intensive problems. These VOs, however, work as disjointed and independent communities with no resource sharing between them. We, in previous work, have proposed a fully decentralized and reconfigurable Inter-Grid framework for resource sharing among such distributed and autonomous Grid systems (Rao et al. in ICCSA, 2006). The specific problem that underlies in such a collaborating Grids system is scheduling of resources as there is very little knowledge about availability of the resources due to the distributed and autonomous nature of the underlying Grid entities. In this paper, we propose a probabilistic and adaptive scheduling algorithm using systemgenerated predictions for Inter-Grid resource sharing keeping collaborating Grid systems autonomous and independent. We first use system-generated job runtime estimates without actually submitting jobs to the target Grid system. Then this job execution estimate is used to predict the job scheduling feasibility on the target system. Furthermore, our proposed algorithm adapted itself to the actual resource behavior and performance. Simulation results are presented to discuss the correctness and accuracy of our proposed algorithm.
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In large-scale collaborative computing, users and resource providers organize various Virtual Organizations (VOs) to share resources and services. A VO organizes other sub-VOs for the purpose of achieving the VO goal, which forms hierarchical VO environments. VO participants agree upon a certain policies, such as resource sharing amount or user accesses. In this letter, we provide an optimal resource sharing mechanism in hierarchical VO environments under resource sharing agreements. The proposed algorithm enhances resource utilization and reduces mean response time of each user.