GENI Mesoscale and The GENI Experiment Engine

1. GENI Mesoscale and The GENI Experiment Engine Trans-Geo Demo Team

3. GENI, JGN-X, FIRE, and the Emergence of the Intercloud • The Internet was about the seamless movement of data… • Internet protocols were fundamentally centered around transfer of bulk data • ftp, http, voip,… • Fundamental to the design of TCP • Later, localized services offered over the wide area • The Intercloud will be about the seamless movement of computation • Design and development of protocols, security procedures, architectures, economic models that permit computation to move to data, rather than the other way around • GENI, FIRE, JGN-X are all early stabs at this…(more later)

4. Implications for Infrastructure • Ubiquitous, isotropic cloud • Ubiquitous: Data collected everywhere, must compute where data is ⇒ compute everywhere • Isotropic: Compute must be able to move between sites, easily – compute must be independent of site. • Adaptive, Virtualizable Network • Currently, networking is application-agnostic (TCP is TCP….) • Need to permit application to allocate network resources just as it now allocates storage, compute resources • Guarantee QoS for high-priority flows, make transmission speeds latency- and loss-independent, virtual networks with admission control…

5. GENI • Ubiquitous cloud with deeply-programmable networking • Ubiquitous Cloud • Abstracted API that can be implemented by any popular cluster manager (Slice Federation Architecture) • Designed for federation • Certificate-based access control (No need for single sign-on, common AUP) • Implementations with fine and deep control of resources (ProtoGENI) • Deeply Programmable Network • Open Flow native • Layer 2 backbone

6. GENI Mesoscale

7. GENI And NSFNet: Back to the Future • GENI today is NSFNet circa 1985 • GENI and the SFA: Set of standards (e.g., TCP/IP) • Mesoscale: Equivalent to NSF Backbone • InstaGENI: Hardware/software instantiation of standards that sites can deploy instantly • Equivalent to VAX 11 running Berkeley Unix • InstaGENI cluster running ProtoGENI and OpenFlow • Other instantiations which are interoperable • ExoGENI (Ilia Baldine, Jeff Chase, RENCI and Duke) • VNode (Aki Nakao, University of Tokyo and NICT)

8. TransGeo: A Model TransCloud Application • Scalable, Ubiquitous Geographic Information System • Open and Public • Anyone can contribute layers • Anyone can host computation • Why GIS? • Large and active community • Characterized by large data sets (mostly satellite images) • Much open-source easily deployable software, standard data formats • Computation naturally partitions and is loosely-coupled • Collaborations across geographic regions and continents • Very pretty…

9. TransGeo Architecture

10. TransGeo Sites (May 2013)

13. Opening up TransGEO: The GENI Experiment Engine • Key Idea: Genericize and make available the infrastructure behind the TransGEO demo • Open to every GENI, FIRE, JGN-X,…experimenter who wants to use it • TransGEO is a trivial application on a generic infrastructure • Perhaps 1000 lines of Python code on top of • Key-Value Store • Layer 2 network • Sandboxed Python programming environment • Messaging Service • Deployment Service • GIS Libraries

14. GENI Experiment EngineMcGeer, Mambretti, Bavier, Coady, Permanent, Long-Running, Distributed File System Permanent, Long-Running, GENI-wide Message Service Permanent, Long-Running, Distributed Python Environment Permanent, world-wide Layer-2 VLANs on high-performance networks All offered in slices All shared by many experimenters Model: Google App Engine Advantage for GENI: Efficient use of resources Advantage for Experimenters: Up and running in no time

15. GENI Experiment Engine Architecture

16. Staged Rollout Permanent Layer-2 Network Summer 2013 Shared Fole System based on (Swift) Summer 2013 First Python Users Fall 2013 Shared Python environment Summer 2014

17. Thanks!