Changes between Version 1 and Version 2 of IGENI

10/26/09 14:04:10 (10 years ago)




    v1 v2  
    3232=== Participating Organizations ===
    34 [  "Northwestern University, International Center for Advanced Internet Research
     34[  "Northwestern University, International Center for Advanced Internet Research
    36 [  "University of Illinois at Chicago, Electronic Visualization Laboratory
     36[  "University of Illinois at Chicago, Electronic Visualization Laboratory
    38 [  "California Institute for Telecommunications and Information Technology (Calit2)"][[BR]]
     38[  "California Institute for Telecommunications and Information Technology (Calit2)"][[BR]]
    4040=== GPO Liason System Engineer ===
    4545== Scope ==
    47 This project will develop a complete environment for researchers to conduct data-intensive experiments in GENI from start (the data collection point) to finish (processing and archiving). [[BR]]
     47This project will define, design and implement  iGENI, a distributed network research infrastructure;   integrate it with current and planned GENI  resources;  and  operate it for the use of GENI researchers conducting experiments that involve multiple aggregates (at multiple sites).  [[BR]]
     49The iGENI infrastructure will be defined in collaboration with the GPO and other GENI projects to expand the controllable transport services available to GENI researchers, and make GENI available to more research communities.  [[BR]]
    49 To do so, this project will extend the GENI/ViSE sensor network (sensornet) testbed at UMass-Amherst and augment GENI Cluster D’s Orca control framework with capabilities for researchers to
    50  (i) obtain data-centric slices that span core sensornet nodes, data center nodes, and, importantly, storage volumes “in the cloud,” [[BR]]
    51  (ii) deploy popular cloud computing programming paradigms to enable simple, but powerful, distributed data processing, and [[BR]]
    52  (iii) execute experiment workflows to explicitly control experiment data flow and resource allocation across a network of components/aggregates. [[BR]]
     51The iGENI infrastructure will connect existing resources with iCAIR involvement (e.g. StarLight) with current GENI backbone transport resources (e.g., Internet2 and NLR layer 2/Ethernet VLANs); current and planned GENI regional transport resources (e.g., BEN, CENIC, and others );  and additional available connections to other research networks (e.g. FIRE).  [[BR]]
    54 The project will build on existing software artifacts in the GENI “ecosystem” and tailor them to the distinct requirements of data-intensive experiments.  While the enhanced software artifacts will generalize to any high-bandwidth data-intensive experiments, the GENI/ViSE sensornet testbed, which collects high-bandwidth data from multiple high-power (virtualized) sensor/actuators, will be the initial data source. [[BR]]
     53The iGENI infrastructure will be integrated as an aggregate with the ORCA control framework in Cluster D.  Through ORCA, available resources in iGENI will be discovered;  services will be setup and managed;  and individual traffic streams will be controlled and managed.  This project will implement interfaces to ORCA that allow dynamic control of network services involving iGENI, associated transport resources and and GENI aggregates.  It will be possible to setup services using prepackaged or customized configurations and topologies. [[BR]]
    56 Our goal by year one is to incorporate commercial cloud computing  services, including storage services, as GENI substrates available for researchers. [[BR]]
    58 Our goal by year two is to enhance GENI’s usefulness by testing and hardening the capability for researchers to request (or load) distributed software platforms on commercial clouds. We will demonstrate the capability using both an MPI stack and Apache’s Hadoop framework, an open-source version of MapReduce and Google File System (GFS).[[BR]]
    60 Our goal by year three is to complete the integration of Gush to discover resources and deploy experiment workflows across data-centric slices in the Orca CF.[[BR]]