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Erschienen in: Cluster Computing 4/2013

01.12.2013

ORTHRUS: a lightweighted block-level cloud storage system

verfasst von: Jian Wan, Jianliang Zhang, Li Zhou, Yicheng Wang, Congfeng Jiang, Yongjian Ren, Jue Wang

Erschienen in: Cluster Computing | Ausgabe 4/2013

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Abstract

Taking advantage of distributed storage technology and virtualization technology, cloud storage systems provide virtual machine clients customizable storage service. They can be divided into two types: distributed file system and block level storage system. There are two disadvantages in existing block level storage system: Firstly, Some of them are tightly coupled with their cloud computing environments. As a result, it’s hard to extend them to support other cloud computing platforms; Secondly, The bottleneck of volume server seriously affects the performance and reliability of the whole system. In this paper we present a lightweighted block-level storage system for clouds—ORTHRUS, based on virtualization technology. We first design the architecture with multiple volume servers and its workflows, which can improve system performance and avoid the problem. Secondly, we propose a Listen-Detect-Switch mechanism for ORTHRUS to deal with contingent volume servers’ failure. At last we design a strategy that dynamically balances load between multiple volume servers. We characterize machine capability and load quantity with black box model, and implement the dynamic load balance strategy which is based on genetic algorithm. Extensive experimental results show that the aggregated I/O throughputs of ORTHRUS are significantly improved (approximately two times of that in Orthrus), and both I/O throughputs and IOPS are also remarkably improved (about 1.8 and 1.2 times, respectively) by our dynamic load balance strategy.

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Metadaten
Titel
ORTHRUS: a lightweighted block-level cloud storage system
verfasst von
Jian Wan
Jianliang Zhang
Li Zhou
Yicheng Wang
Congfeng Jiang
Yongjian Ren
Jue Wang
Publikationsdatum
01.12.2013
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 4/2013
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-012-0234-7

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