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Towards Understanding the Runtime Configuration Management of Do-It-Yourself Content Delivery Network Applications over Public Clouds
School of Computer Science, Australian National University and NICTA.
LuleƄ University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-3489-7429
CSIRO Computational Informatics, Canberra.
CSIRO Computational Informatics, Canberra.
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2014 (English)In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 37, 297-308 p.Article in journal (Refereed) Published
Abstract [en]

Cloud computing is a new paradigm shift which enables applications and related content (audio, video, text, images, etc.) to be provisioned in an on-demand manner and being accessible to anyone anywhere in the world without the need for owning expensive computing and storage infrastructures. Interactive multimedia content-driven applications in the domains of healthcare, aged-care, and education have emerged as one of the new classes of big data applications. This new generation of applications need to support complex content operations including production, deployment, consumption, personalisation, and distribution. However, to efficiently provision these applications on the Cloud data centres, there is a need to understand their run-time resource configurations. For example: (i) where to store and distribute the content to and from driven by end-user Service Level Agreements (SLAs)? (ii) how many content distribution servers to provision? and (iii) what Cloud VM configuration (number of instances, types, speed, etc.) to provision? In this paper, we present concepts and factors related to engineering such content-driven applications over public Clouds. Based on these concepts and factors, we propose a performance evaluation methodology for quantifying and understanding the runtime configuration these classes of applications. Finally, we conduct several benchmark driven experiments for validating the feasibility of the proposed methodology.

Place, publisher, year, edition, pages
2014. Vol. 37, 297-308 p.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
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URN: urn:nbn:se:ltu:diva-5130DOI: 10.1016/j.future.2013.12.019Local ID: 32606a40-6d6f-4973-98c3-baf8bee9a213OAI: oai:DiVA.org:ltu-5130DiVA: diva2:978004
Note
Validerad; 2014; 20140110 (karan)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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Mitra, Karan

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