Predicting the cost and benefit of adapting data parallel applications in clusters
Journal of Parallel and Distributed Computing
PUNCH: An architecture for Web-enabled wide-area network-computing
Cluster Computing
Enhanced Algorithms for Multi-site Scheduling
GRID '02 Proceedings of the Third International Workshop on Grid Computing
Predicting Application Run Times Using Historical Information
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
A Self-Tuning Job Scheduler Family with Dynamic Policy Switching
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Adaptive Computing on the Grid Using AppLeS
IEEE Transactions on Parallel and Distributed Systems
A Dynamic Matching and Scheduling Algorithm for Heterogeneous Computing Systems
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
Matchmaking: Distributed Resource Management for High Throughput Computing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
Toward a Common Component Architecture for High-Performance Scientific Computing
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Predictive Application-Performance Modeling in a Computational Grid Environment
HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Distributed Job Scheduling on Computational Grids Using Multiple Simultaneous Requests
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Lightweight Self-Organizing Frameworks for Metacomputing
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Towards an Economy-Based Optimisation of File Access and Replication on a Data Grid
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
The Architecture of the Remos System
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
A Study of Deadline Scheduling for Client-Server Systems on the Computational Grid
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
Adaptive middleware for high-end network services
Adaptive middleware for high-end network services
Analyzing Market-Based Resource Allocation Strategies for the Computational Grid
International Journal of High Performance Computing Applications
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Network service-based computation is a promising paradigm for both scientific and engineering, and enterprise computing. The network service allows users to focus on their application and obtain services when needed, simply by invoking the service across the network. In this paper, we show that an adaptive, general-purpose run-time infrastructure in support of effective resource management can be built for a wide range of high-end network services running in a single-site cluster and in a Grid. The primary components of the run-time infrastructure are: (1) dynamic performance prediction; (2) adaptive intra-site resource management; and (3) adaptive inter-site resource management. The novel aspect of our approach is that the run-time system is able to dynamically select the most appropriate performance predictor or resource management strategy over time. This capability not only improves the performance, but also makes the infrastructure reusable across different high-end services. To evaluate the effectiveness and applicability of our approach, we have transformed two different classes of high-end applications-data parallel and distributed applications-into network services using the infrastructure. The experimental results show that the network services running on the infrastructure significantly reduce the overall service times under dynamically varying circumstances.