Scheduling with Advanced Reservations
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
GARA: a uniform quality of service architecture
Grid resource management
Advance Reservation and Co-Allocation Protocol for Grid Computing
E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
An Interoperable, Standards-Based Grid Resource Broker and Job Submission Service
E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
On the impact of reservations from the grid on planning-based resource management
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
An adaptive multisite mapping for computationally intensive grid applications
Future Generation Computer Systems
Concurrent negotiation and coordination for grid resource coallocation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Using network information to perform meta-scheduling in advance in grids
EuroPar'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part I
Network-aware meta-scheduling in advance with autonomous self-tuning system
Future Generation Computer Systems
Dynamic resource matching for multi-clusters based on an ontology-fuzzy approach
HPCS'09 Proceedings of the 23rd international conference on High Performance Computing Systems and Applications
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Co-allocation and co-reservation is a key capability of Grid schedulers for supporting some complex Grid applications, e.g., workflow. The chief enabling technology of co-allocation and co-reservation is Advance Reservation (AR), which is typically implemented by local Resource Management Systems (RMSs). As at present only a limited number of RMSs can support AR, and most of them use individual interface formats, it is rather difficult for Grid schedulers to manage Grid ARs across heterogeneous RMSs, including AR-incapable ones, through a uniform interface. In this paper we propose a Grid AR framework which can address the issue by means of a Grid AR manager that is able to externalize the AR functionality from local RMSs. An advanced Grid AR algorithm is implemented in the Grid AR manager, and a local AR API and Grid AR API is respectively defined to standardize the interaction between the Grid AR manager and local RMSs, as well as between high level Grid scheduler components and Grid AR manager. Based on a plugin architecture, the Grid AR framework is able to incorporate different types of local RMSs to implement Grid AR functionalities, irrespective of whether local RMSs support AR or not.