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The GENI Book pp 279-315 | Cite as

ExoGENI: A Multi-Domain Infrastructure-as-a-Service Testbed

  • Ilya Baldin
  • Jeff Chase
  • Yufeng Xin
  • Anirban Mandal
  • Paul Ruth
  • Claris Castillo
  • Victor Orlikowski
  • Chris Heermann
  • Jonathan Mills
Chapter

Abstract

This chapter describes ExoGENI, a multi-domain testbed infrastructure built using the ORCA control framework. ExoGENI links GENI to two advances in virtual infrastructure (IaaS) services outside of GENI: open cloud computing (OpenStack) and dynamic circuit fabrics. It orchestrates a federation of independent cloud sites and circuit providers through their native IaaS interfaces, and links them to other GENI tools and resources. ExoGENI slivers are instances of basic IaaS resources: variously sized virtual machines, bare-metal nodes, iSCSI block storage volumes, and Layer 2 network links with optional OpenFlow control.

ExoGENI offers a powerful unified hosting platform for deeply networked, multi-domain, multi-site cloud applications. ExoGENI operates its own stitching engine and Layer 2 (L2) network exchanges that work in concert to interconnect the sites with dynamic point-to-point and multi-point L2 links via multiple circuit providers. It also supports stitchports—named attachment points enabling direct L2 connections to resources outside the system’s control.ExoGENI is seeding a larger, evolving platform linking third-party cloud sites, transport networks, new resource types, and other infrastructure services. It facilitates real-world deployment of innovative distributed services, leading to a new vision of a future federated, more resilient, and deeply networked cyber-infrastructure. This chapter explores the unique features of ExoGENI and, in particular, how it differs from other GENI testbeds.

Keywords

Virtual Machine Work Node Virtual Topology Circuit Service Block Device 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We thank NSF, IBM, and the GENI Project Office (GPO) at BBN-Raytheon for their support. Many colleagues at GPO and other GENI projects have helped work through issues relating to ExoGENI. We’d like to thank our colleagues from the EU: University of Amsterdam SNE Group and Ghent University/iMinds for their help and code contributions.

This work is supported by the US National Science Foundation through the GENI initiative and NSF awards OCI-1032873, CNS-0910653, and CNS-0720829; by IBM and NetApp; and by the State of North Carolina through RENCI.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ilya Baldin
    • 1
  • Jeff Chase
    • 2
  • Yufeng Xin
    • 1
  • Anirban Mandal
    • 1
  • Paul Ruth
    • 1
  • Claris Castillo
    • 1
  • Victor Orlikowski
    • 2
  • Chris Heermann
    • 1
  • Jonathan Mills
    • 3
  1. 1.Renaissance Computing Institute (RENCI)/UNC Chapel HillChapel HillUSA
  2. 2.Duke UniversityDurhamUSA
  3. 3.NASA Center for Climate SimulationGoddard Space Flight CenterGreenbeltUSA

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