Demo abstract: Enabling high-throughput big data transfers across campus networks

Sergio Rivera, Jacob Chappell, Mami Hayashida, Andrew Groenewold, Peter Oostema, Caleb Voss, Hussamuddin Nasir, Charles Carpenter, Yongwook Song, Zongming Fei, James Griffioen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Big Data transfers are increasingly plagued by middlebox bottlenecks such as NAT boxes, firewalls, and intrusion detection systems that prevent large data transfers from achieving maximal throughput across the campus network. Science DMZs have historically been used to solve this problem. We are developing a Software Defined Networking (SDN) campus network that achieves the same benefits - by allowing privileged flows to bypass middleboxes - without the limitations and downsides of Science DMZs. To evaluate our approach and develop a prototype implementation, we created a campus-like lab-based physical network using Aruba switches that support running multiple OpenFlow (virtual) instances per physical chassis. We will demonstrate the control software used to drive the testbed and the performance improvement for big data transfers under our approach.

Original languageEnglish
Title of host publication2017 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2017
Pages954-955
Number of pages2
ISBN (Electronic)9781538627846
DOIs
StatePublished - Nov 20 2017
Event2017 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2017 - Atlanta, United States
Duration: May 1 2017May 4 2017

Publication series

Name2017 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2017

Conference

Conference2017 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2017
Country/TerritoryUnited States
CityAtlanta
Period5/1/175/4/17

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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