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Anticipating Requests to Improve Performance and Reduce Costs in Cloud Storage

Authors:

Hylson Vescovi Netto,

Lau Cheuk Lung,

Tulio Alberton Ribeiro,

Miguel Correia,

Aldelir Fernando LuizAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 43, Issue 3

Pages 21 - 24

https://doi.org/10.1145/2847220.2847226

Published: 19 November 2015 Publication History

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Abstract

Clouds are a suitable place to store data with scalability and financial flexibility. However, it is difficult to ensure the reliability of the data stored in a cloud. Byzantine fault tolerance can improve reliability, but at a high cost. This paper presents a technique that anticipates requests in order to reduce that cost. We show that this technique improves the performance in comparison with related works and maintains the desired data reliability.

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Index Terms

Anticipating Requests to Improve Performance and Reduce Costs in Cloud Storage
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles

Index terms have been assigned to the content through auto-classification.

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cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 43, Issue 3

December 2015

89 pages

ISSN:0163-5999

DOI:10.1145/2847220

Editor:
Nidhi Hegde
Bell Labs France, Alcatel-Lucent Centre de Villarceaux Route de Villejust, Nozay, France

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Association for Computing Machinery

New York, NY, United States

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Published: 19 November 2015

Published in SIGMETRICS Volume 43, Issue 3

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Cloud Storage as the Infrastructure of Cloud Computing

Middleware enabled data sharing on cloud storage services

Block storage scheduling based on SLA in cloud storage systems

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Recommendations

Cloud Storage as the Infrastructure of Cloud Computing

Middleware enabled data sharing on cloud storage services

Block storage scheduling based on SLA in cloud storage systems

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