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Brinkmann, André;Salzwedel, Kay;Scheideler, Christian:

Efficient, Distributed Data Placement Strategies for Storage Area Networks .

In: Proceedings of the 12th ACM Symposium on Parallel Algorithms and Architectures (SPAA), pp. 119 - 128, Bar Harbor, Maine, USA, July 9 - 13, 2000

Abstract

In the last couple of years a dramatic growth of enterprise data storage capacity can be observed. As a result, new strategies have been sought that allow servers and storage being centralized to better manage the explosion of data and the overall cost of ownership. Nowadays, a common approach is to combine storage devices into a dedicated network that is connected to LANs and/or servers. Such networks are usually called storage area networks (SAN). A very important aspect for these networks is scalability. If a SAN undergoes changes (for instance, due to insertions or removals of disks), it may be necessary to replace data in order to allow an e±cient use of the system. To keep the influence of data replacements on the performance of the SAN small, this should be done as efficiently as possible.

In this paper, we investigate the problem of evenly distributing and efficiently locating data in dynamically changing SANs. We consider two scenarios: (1) all disks have the same capacity, and (2) the capacities of the disks are allowed to be arbitrary. For both scenarios, we present placement strategies capable of locating blocks efficiently and that are able to quickly adjust the data placement to insertions or removals of disks or data blocks. Furthermore, we study how the performance of our placement strategies changes if we allow to waste a certain amount of capacity of the disks.

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Bibtex

@inproceedings{hniid=58,
author = {Brinkmann, André and Salzwedel, Kay and Scheideler, Christian},
title = {Efficient, Distributed Data Placement Strategies for Storage Area Networks },
booktitle = {Proceedings of the 12th ACM Symposium on Parallel Algorithms and Architectures (SPAA)},
pages = {119 - 128},
address = {Bar Harbor, Maine, USA},
month = {9~-~13~} # jul,
year = {2000},
}

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https://www.hni.uni-paderborn.de/pub/58