Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Enabling Performance Intelligence for Application Adaptation in the Future Internet

  • Calyam, Prasad (OARnet/Ohio Supercomputer Center, The Ohio State University) ;
  • Sridharan, Munkundan (OARnet/Ohio Supercomputer Center, The Ohio State University) ;
  • Xu, Yingxiao (OARnet/Ohio Supercomputer Center, The Ohio State University) ;
  • Zhu, Kunpeng (OARnet/Ohio Supercomputer Center, The Ohio State University) ;
  • Berryman, Alex (OARnet/Ohio Supercomputer Center, The Ohio State University) ;
  • Patali, Rohit (OARnet/Ohio Supercomputer Center, The Ohio State University) ;
  • Venkataraman, Aishwarya (OARnet/Ohio Supercomputer Center, The Ohio State University)
  • Received : 2011.05.13
  • Published : 2011.12.31
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Abstract

Today's Internet which provides communication channels with best-effort end-to-end performance is rapidly evolving into an autonomic global computing platform. Achieving autonomicity in the Future Internet will require a performance architecture that (a) allows users to request and own 'slices' of geographically-distributed host and network resources, (b) measures and monitors end-to-end host and network status, (c) enables analysis of the measurements within expert systems, and (d) provides performance intelligence in a timely manner for application adaptations to improve performance and scalability. We describe the requirements and design of one such "Future Internet performance architecture" (FIPA), and present our reference implementation of FIPA called 'OnTimeMeasure.' OnTimeMeasure comprises of several measurement-related services that can interact with each other and with existing measurement frameworks to enable performance intelligence. We also explain our OnTimeMeasure deployment in the global environment for network innovations (GENI) infrastructure collaborative research initiative to build a sliceable Future Internet. Further, we present an applicationad-aptation case study in GENI that uses OnTimeMeasure-enabled performance intelligence in the context of dynamic resource allocation within thin-client based virtual desktop clouds. We show how a virtual desktop cloud provider in the Future Internet can use the performance intelligence to increase cloud scalability, while simultaneously delivering satisfactory user quality-of-experience.

Keywords

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