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Content-aware traffic engineering

Published:11 June 2012Publication History

ABSTRACT

Recent studies show that a large fraction of Internet traffic is originated by Content Providers (CPs) such as content distribution networks and hyper-giants. To cope with the increasing demand for content, CPs deploy massively distributed server infrastructures. Thus, content is available in many network locations and can be downloaded by traversing different paths in a network. Despite the prominent server location and path diversity, the decisions on how to map users to servers by CPs and how to perform traffic engineering by ISPs, are independent. This leads to a lose-lose situation as CPs are not aware about the network bottlenecks nor the location of end-users, and the ISPs struggle to cope with rapid traffic shifts caused by the dynamic CP server selection process.

In this paper we propose and evaluate Content-aware Traffic Engineering (CaTE), which dynamically adapts the traffic demand for content hosted on CPs by utilizing ISP network information and end-user location during the server selection process. This leads to a win-win situation because CPs are able to enhance their end-user to server mapping and ISPs gain the ability to partially influence the traffic demands in their networks. Indeed, our results using traces from a Tier-1 ISP show that a number of network metrics can be improved when utilizing CaTE.

References

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  1. Content-aware traffic engineering

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      • Published in

        cover image ACM Conferences
        SIGMETRICS '12: Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
        June 2012
        450 pages
        ISBN:9781450310970
        DOI:10.1145/2254756
        • cover image ACM SIGMETRICS Performance Evaluation Review
          ACM SIGMETRICS Performance Evaluation Review  Volume 40, Issue 1
          Performance evaluation review
          June 2012
          433 pages
          ISSN:0163-5999
          DOI:10.1145/2318857
          Issue’s Table of Contents

        Copyright © 2012 Authors

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 11 June 2012

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        Overall Acceptance Rate459of2,691submissions,17%

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