Dynamic Allocation and Efficient Distribution of Data Among Multiple Clouds Using Network Coding

Research output: Research - peer-reviewArticle in proceeding

Abstract

Distributed storage has attracted large interest lately from both industry and researchers as a flexible, cost-efficient, high performance, and potentially secure solution for geographically distributed data centers, edge caching or sharing storage among users. This paper studies the benefits of random linear network coding to exploit multiple commercially available cloud storage providers simultaneously with the possibility to constantly adapt to changing cloud performance in order to optimize data retrieval times. The main contribution of this paper is a new data distribution mechanisms that cleverly stores and moves data among different clouds in order to optimize performance. Furthermore, we investigate the trade-offs among storage space, reliability and data retrieval speed for our proposed scheme. By means of real-world implementation and measurements using well-known and publicly accessible cloud service providers, we can show close to 9x less network use for the adaptation compared to more conventional dense recoding approaches, while maintaining similar download time performance and the same reliability.
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Distributed storage has attracted large interest lately from both industry and researchers as a flexible, cost-efficient, high performance, and potentially secure solution for geographically distributed data centers, edge caching or sharing storage among users. This paper studies the benefits of random linear network coding to exploit multiple commercially available cloud storage providers simultaneously with the possibility to constantly adapt to changing cloud performance in order to optimize data retrieval times. The main contribution of this paper is a new data distribution mechanisms that cleverly stores and moves data among different clouds in order to optimize performance. Furthermore, we investigate the trade-offs among storage space, reliability and data retrieval speed for our proposed scheme. By means of real-world implementation and measurements using well-known and publicly accessible cloud service providers, we can show close to 9x less network use for the adaptation compared to more conventional dense recoding approaches, while maintaining similar download time performance and the same reliability.
Original languageEnglish
Title of host publicationCloud Networking (CloudNet), 2014 IEEE 3rd International Conference on
PublisherIEEE
Publication date2014
Pages90 - 95
ISBN (Print)978-1-4799-2730-2
DOI
StatePublished - 2014
Publication categoryResearch
Peer-reviewedYes
EventThird IEEE International Conference on Cloud Networking - , Luxembourg
Duration: 8 Oct 2014 → …

Conference

ConferenceThird IEEE International Conference on Cloud Networking
LandLuxembourg
Periode08/10/2014 → …
SeriesIEEE International Conference on Cloud Networking

Projects

ID: 201947067