A recursive-adjustment co-allocation scheme in data grid environments

Authors:
Chao-Tung Yang;I-Hsien Yang;Kuan-Ching Li;Ching-Hsien Hsu
Affiliations:
High Performance Computing Laboratory, Department of Computer Science and Information Engineering, Tunghai University, Taichung, Taiwan, ROC;High Performance Computing Laboratory, Department of Computer Science and Information Engineering, Tunghai University, Taichung, Taiwan, ROC;Parallel and Distributed Processing Center, Department of Computer Science and Information Management, Providence University, Taichung, Taiwan, ROC;Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu, Taiwan
Venue:
ICA3PP'05 Proceedings of the 6th international conference on Algorithms and Architectures for Parallel Processing
Year:
2005

Citing 16
Cited 4

The network weather service: a distributed resource performance forecasting service for metacomputing

Future Generation Computer Systems - Special issue on metacomputing
File and Object Replication in Data Grids

Cluster Computing
Data management and transfer in high-performance computational grid environments

Parallel Computing - Parallel data-intensive algorithms and applications
Data Management in an International Data Grid Project

GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
Predicting the Performance of Wide Area Data Transfers

IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Giggle: a framework for constructing scalable replica location services

Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Replica Selection in the Globus Data Grid

CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
Resource Co-Allocation in Computational Grids

HPDC '99 Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing
Predicting Sporadic Grid Data Transfers

HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
A Performance Study of Monitoring and Information Services for Distributed Systems

HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Secure, Efficient Data Transport and Replica Management for High-Performance Data-Intensive Computing

MSS '01 Proceedings of the Eighteenth IEEE Symposium on Mass Storage Systems and Technologies
Grid Information Services for Distributed Resource Sharing

HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
Enabling the Co-Allocation of Grid Data Transfers

GRID '03 Proceedings of the 4th International Workshop on Grid Computing
Using Regression Techniques to Predict Large Data Transfers

International Journal of High Performance Computing Applications
Introduction to grid computing with globus

Introduction to grid computing with globus
Performance analysis of applying replica selection technology for data grid environments

PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies

Implementation of a dynamic adjustment mechanism with efficient replica selection in data grid environments

Proceedings of the 2006 ACM symposium on Applied computing
Redundant parallel file transfer with anticipative recursively-adjusting scheme in data grids

ICA3PP'07 Proceedings of the 7th international conference on Algorithms and architectures for parallel processing
A dynamic adjustment strategy for file transformation in data grids

NPC'07 Proceedings of the 2007 IFIP international conference on Network and parallel computing
Metropolitan-scale grid environment: the implementation and applications of TIGER grid

ISPA'06 Proceedings of the 2006 international conference on Frontiers of High Performance Computing and Networking

Quantified Score

Hi-index	0.00

Visualization

Abstract

The co-allocation architecture was developed in order to enable parallel downloads of datasets from multiple servers. Several co-allocation strategies have been coupled and used to exploit rate differences among various client-server links and to address dynamic rate fluctuations by dividing files into multiple blocks of equal sizes. However, a major obstacle, the idle time of faster servers having to wait for the slowest server to deliver the final block, makes it important to reduce differences in finish time among replica servers. In this paper, we propose a dynamic co-allocation scheme, namely Recursive-Adjustment Co-Allocation scheme, to improve the performance of data transfer in Data Grids. Our approach reduces the idle time spent waiting for the slowest server and decreases data transfer completion time.