V I SE/D I C LOUD S TATUS J ULY 28 TH, 2011 Michael Zink ECE Department University of Massachusetts Amherst.

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Presentation transcript:

V I SE/D I C LOUD S TATUS J ULY 28 TH, 2011 Michael Zink ECE Department University of Massachusetts Amherst

V I SE S TATUS Project’s Official Ending September 1st Assembled/deployed 3 off-the-grid radar nodes Collaborating w/UPRM on similar testbed Also use larger nodes (Umass+Oklahoma) Integrated virtualized nodes with Orca GENI Alpha Demo Demonstrated Orca orchestration of setup of radar  forecast workflow across radars, NLR, cloud, RENCI, etc. to

V I SE S TATUS Project’s Official Ending September 1 st Inspired lots of research papers Predicting solar/wind generation (SECON10, SmartGridComm11) Market-based resource allocation for GENI (AAMAS10) Sensor Virtualization (MMSys11,TridentCom10) Cloud Orchestration w/Radar sensors (MENS10,LANMAN10) Future Plans Continue to use ViSE as part of DiCloud (funding permitting) Focus on user applications MyCasting: highly localized forecasts (for GPS coordinates) computed on-demand in the cloud and sent to mobile

V I SE S TATUS Benefits of GENI GENI/Orca software/support vital for allocating diverse resources We focused on “virtualizing” radars and using radar  forecast workflows with Orca Didn’t focus on higher-level resource allocation and coordination software Using Orca software extensions and packages for local Eucalyptus cluster Wouldn’t have otherwise been able to coordinate allocation of so many resources across so many sites Radars, VMs, network links in MA, IL, VA, NC, etc.

V I SE S TATUS ViSE Plans Continue to develop larger user-base Convince researchers radars are interesting source of high-bandwidth data for large-scale networks Continue to use ViSE as part of DiCloud (funding permitting) Focus on user-oriented applications MyCasting: highly localized forecasts (for GPS coordinates) computed on-demand in the cloud and sent to mobile

D I C LOUD S TATUS DiCloud Plans Integrate Gush-Orca-DiCloud (working with Jeannie+Ilia) Make it easier for researchers to leverage DiCloud Implement our radar  forecasting workflows as Gush applications Use DiCloud as part of MyCasting work Continue to develop DiCloud software Accounting and allocation for GENI substrates to safely use Amazon resources on a budget