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Reducing server and network load with shared buffering

Published: 10 December 2012 Publication History

Abstract

Today, content replication methods are common ways of reducing the network and servers load. Present content replication solutions have different problems, including the need for pre-planning and management, and they are ineffective in case of sudden traffic spikes. In spite of these problems, content replication methods are more popular today than ever, simply because of an increasing need for load reduction. In this paper, we propose a shared buffering model that, unlike current proxy-based content replication methods, is native to the network and can be used to alleviate the stress of sudden traffic spikes on servers and the network. We outline the characteristics of a new transport protocol that uses the shared buffers to offload the server work to the network or reduce the pressure on the overloaded links.

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Cited By

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  • (2016)Transport Control Strategies in Named Data Networking: A SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2016.252816418:3(2052-2083)Online publication date: 1-Jul-2016
  • (2015)Reduce VM migration in bandwidth oversubscribed cloud data centres2015 IEEE 12th International Conference on Networking, Sensing and Control10.1109/ICNSC.2015.7116024(140-145)Online publication date: Apr-2015

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    cover image ACM Conferences
    CSWS '12: Proceedings of the 2012 ACM workshop on Capacity sharing
    December 2012
    66 pages
    ISBN:9781450317801
    DOI:10.1145/2413219
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    Publication History

    Published: 10 December 2012

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    Author Tags

    1. caching
    2. resource management
    3. transport protocols

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    CSWS '12 Paper Acceptance Rate 9 of 17 submissions, 53%;
    Overall Acceptance Rate 19 of 40 submissions, 48%

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    • (2016)Transport Control Strategies in Named Data Networking: A SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2016.252816418:3(2052-2083)Online publication date: 1-Jul-2016
    • (2015)Reduce VM migration in bandwidth oversubscribed cloud data centres2015 IEEE 12th International Conference on Networking, Sensing and Control10.1109/ICNSC.2015.7116024(140-145)Online publication date: Apr-2015

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