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Data Scheduling for Large Scale Distributed Applications (2007)
| Venue: | PROCEEDINGS OF THE 5TH ICEIS DOCTORAL CONSORTIUM, IN CONJUNCTION WITH THE INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS (ICEIS’07 |
| Citations: | 20 - 16 self |
BibTeX
@INPROCEEDINGS{Balman07datascheduling,
author = {Mehmet Balman and Tevfik Kosar},
title = {Data Scheduling for Large Scale Distributed Applications},
booktitle = {PROCEEDINGS OF THE 5TH ICEIS DOCTORAL CONSORTIUM, IN CONJUNCTION WITH THE INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS (ICEIS’07},
year = {2007},
publisher = {}
}
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Abstract
Current large scale distributed applications studied by large research communities result in new challenging problems in widely distributed environments. Especially, scientific experiments using geographically separated and heterogeneous resources necessitated transparently accessing distributed data and analyzing huge collection of information. We focus on data-intensive distributed computing and describe data scheduling approach to manage large scale scientific and commercial applications. We identify parameters affecting data transfer and also analyze different scenarios for possible use cases of data placement tasks to discover key attributes for performance optimization. We are planning to define crucial factors in data placement in widely distributed systems and develop a strategy to schedule data transfers according to characteristics of dynamically changing distributed environments.
Keyphrases
large scale distributed application data scheduling data transfer huge collection large research community large scale possible use case current large scale describe data performance optimization data placement task key attribute commercial application heterogeneous resource scientific experiment crucial factor data placement analyze different scenario
