Changes between Version 3 and Version 4 of GENIExperimenter/GENIWebinars/DeployingNetworkAwareApplicationsInGENI


Ignore:
Timestamp:
06/10/16 10:07:30 (5 years ago)
Author:
Ben Newton
Comment:

--

Legend:

Unmodified
Added
Removed
Modified
  • GENIExperimenter/GENIWebinars/DeployingNetworkAwareApplicationsInGENI

    v3 v4  
    88=== Abstract ===
    99
    10 We will discuss the requirements and design of a “Future Internet Performance Architecture” (FIPA), and present a hands-on demo that shows how to use our a reference implementation of FIPA that we developed called ‘!OnTimeMeasure’. !OnTimeMeasure comprises of several measurement related services that can interact with each other to enable performance intelligence within applications. We will show how !OnTimeMeasure can be deployed in the Global Environment for Network Innovations (GENI) infrastructure, and integrated within an application-adaptation scenario. We will present a case study example 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 can use the performance intelligence within a GENI slice to increase cloud scalability, while simultaneously delivering satisfactory user quality-of-experience.
     10We will discuss the requirements and design of a “Future Internet Performance Architecture” (FIPA), and present a hands-on demo that shows how to use a reference implementation of FIPA that we developed called ‘!OnTimeMeasure’. !OnTimeMeasure is comprised of several measurement related services that can interact with each other to enable performance intelligence within applications. We will show how !OnTimeMeasure can be deployed in the Global Environment for Network Innovations (GENI) infrastructure, and integrated within an application-adaptation scenario. Also we will present a case study in GENI that uses !OnTimeMeasure-enabled performance intelligence in the context of dynamic resource allocation within thin-client based virtual desktop clouds. Lastly, we will show how a virtual desktop cloud provider can use the performance intelligence within a GENI slice to increase cloud scalability, while simultaneously delivering satisfactory user quality-of-experience.
    1111
    1212