A bridging model for parallel computation
Communications of the ACM
A worldwide flock of Condors: load sharing among workstation clusters
Future Generation Computer Systems - Special issue: resource management in distributed systems
High-throughput resource management
The grid
Gallop: the benefits of wide-area computing for parallel processing
Journal of Parallel and Distributed Computing
A network performance tool for grid environments
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Future Generation Computer Systems - Special issue on metacomputing
High Performance Cluster Computing: Architectures and Systems
High Performance Cluster Computing: Architectures and Systems
A Resource Management Architecture for Metacomputing Systems
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
BRITE: Universal Topology Generation from a User''s Perspective
BRITE: Universal Topology Generation from a User''s Perspective
Grid Information Services for Distributed Resource Sharing
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
A decoupled scheduling approach for Grid application development environments
Journal of Parallel and Distributed Computing - Special issue on computational grids
BRITE: An Approach to Universal Topology Generation
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
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Rapid advances in network and computer technologies are making networked computers, organized in the form of Grid, an appealing vehicle for cost-effective parallel computing. But how to handle efficiently the communications in scheduling is still a main obstacle to using these resources. In this paper, we tackle this problem by partitioning resources into groups in a parallel and distributed fashion. Resources with good communication performance to each other will be clustered into a same group. Based on our observation that communication latencies between adjacent resources are much less than those between non-adjacent ones with high possibility, flooding with a small TTL (Time-To-Live) can inherently exploit the proximity property between resources, which improves greatly the efficiency of our partitioning work. Our distributed resource management method can fit well for environments with large-scale resources such as Grid.