Software defined transport

Hong, Chi-Yao

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https://hdl.handle.net/2142/72760 Copy

Description

Title

Software defined transport

Author(s)

Hong, Chi-Yao

Issue Date

2015-01-21

Director of Research (if dissertation) or Advisor (if thesis)

• Godfrey, P. Brighten
• Caesar, Matthew

Doctoral Committee Chair(s)

Godfrey, P. Brighten

Committee Member(s)

• Caesar, Matthew
• Nahrstedt, Klara
• Gupta, Indranil
• Feamster, Nick

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Data Center
• Flow Scheduling
• Transport Rate Control
• Deadline
• Network Utilization
• Software Defined Networking

Abstract

We advocate a software defined transport (SDT) architecture in which a transport controller schedules and dynamically re-schedules the flow sending rates based on current network conditions and the network operator's goals. This dissertation shows that this architecture provides both high flexibility, by allowing the operator to implement new transport policies as needed, and fine-grained flow control, by optimizing network resource allocation at flow-level in real time. We begin with proposing a fine-grained flow scheduling protocol to complete flows quickly and meet flow deadlines. Through extensive packet-level and flow-level simulation, we demonstrate that fine-grained flow control can significantly reduce mean flow completion times by 30% or more compared with TCP, RCP, and D3. We next design a software-driven controller which centrally allocates network resource such as bandwidth and routing paths for flexibility. In particular, we develop a prototype of our design for inter-datacenter wide area networks to achieve nearly optimal network utilization and service-level fairness. After that, we address network update problem to ensure bandwidth requirements during network updates subject to network capacity and switch memory constraints. Finally, we design and implement a fast, fine-grained flow-rate controller for data center networks. We show this design provides high scalability, by rate-controlling 95% of bytes of a cluster with several thousand servers within hundreds of milliseconds with a multi-threaded resource allocation algorithm, and application-level improvement, by reducing average shuffling times of MapReduce workload by 12-20%.

Graduation Semester

2014-12

Permalink

http://hdl.handle.net/2142/72760

Copyright and License Information

Copyright 2014 Chi-Yao Hong

Owning Collections