Dragon: Scalable, Flexible, and Efficient Traffic Engineering in Software Defined ISP Networks

To optimize network cost, performance, and reliability, SDN advocates for centralized traffic engineering (TE) that enables more efficient path and egress point selection as well as bandwidth allocation. In this paper, we argue SDN-based TE for ISP networks can be very challenging. First, ISP networ...

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Bibliographic Details
Published in:IEEE journal on selected areas in communications 2018-12, Vol.36 (12), p.2744-2756
Main Authors: Moradi, Mehrdad, Zhang, Ying, Morley Mao, Z., Manghirmalani, Ravi
Format: Article
Language:English
Subjects:
Control systems
Egress
framework
hierarchical
ISP
Linear programming
Network reliability
Network topology
Optimization
Prototyping
recursive
Reliability engineering
Routing (telecommunications)
Scalability
SDN
Software defined networking
Software engineering
Software reliability
Switches
Switching theory
Three dimensional models
Throughput
Traffic control
Traffic engineering
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Summary:To optimize network cost, performance, and reliability, SDN advocates for centralized traffic engineering (TE) that enables more efficient path and egress point selection as well as bandwidth allocation. In this paper, we argue SDN-based TE for ISP networks can be very challenging. First, ISP networks often are very large in size, imposing significant scalability challenges to the centralized TE. Second, ISP networks usually have diverse types of links, switches, and cost models, leading to a complex combination of optimizations. Third, ISP networks not only have many choices of internal paths but also include rich selections of egress points and interdomain routes, unlike cloud/enterprise networks. To overcome these challenges, we present a novel TE application framework, called Dragon, for existing SDN control planes. To address the scalability challenge, Dragon consists of hierarchical and recursive TE algorithms and mechanisms that divide flow optimization problems into subtasks and execute them in parallel. Further, Dragon allows ISPs to express diverse objectives for different parts of their network. Finally, we extend Dragon to jointly optimize the selection of intradomain and interdomain paths. Using extensive evaluation on real topologies and prototyping with SDN controller and switches, we demonstrate that Dragon outperforms existing TE methods both in speed and optimality.
ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2018.2871312