G-lambda: coordination of a grid scheduler and lambda path service over GMPLS
Future Generation Computer Systems - IGrid 2005: The global lambda integrated facility
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
Proceedings of the first international conference on Networks for grid applications
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Co-scheduling with user-settable reservations
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
Proceedings of the first international conference on Networks for grid applications
An adaptive multisite mapping for computationally intensive grid applications
Future Generation Computer Systems
JSSPP'10 Proceedings of the 15th international conference on Job scheduling strategies for parallel processing
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
CANPRO: a conflict-aware protocol for negotiation of cloud resources and services
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
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For high performance parallel computing on actual Grids, one of the important issues is to co-allocate the distributed resources that are managed by various local schedulers with advance reservation. To address the issue, we proposed and developed the GridARS resource co-allocation framework, and a general advance reservation protocol that uses WSRF/GSI and a two-phased commit (2PC) protocol to enable a generic and secure advance reservation process based on distributed transactions, and provides the interface module for various existing resource schedulers. To confirm the effectiveness of GridARS, we describe the performance of a simultaneous reservation process and a case study of GridARS grid co-allocation over transpacific computing and network resources. Our experiments showed that: 1) the GridARS simultaneous 2PC reservation process is scalable and practical and 2) GridARS can coallocate distributed resources managed by various local schedulers stably.