Performance analysis for a service delivery platform in software defined network

Qiang Duan, Mengxi Zeng, Jun Huang, Cong Cong Xing

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Software Defined Networking (SDN) is an emerging networking paradigm that is expected to play a significant role in future networks. Although exciting progress has been made in research and development of SDN technologies, application of this new networking paradigm in large scale networks with heterogeneous autonomous domains, such as the Internet, is still a challenging issue that calls for a new service delivery platform offering a high-level abstraction for network programmability and inter-domain collaboration. In this paper, we first present a service delivery platform that employs the Network-as-a-Service (NaaS) notion for end-to-end service provisioning in SDN. Then we propose a novel modeling and analysis method for evaluating performance of the service delivery platform. The proposed analysis method addresses the challenges brought in by network abstraction and domain diversity in the service delivery platform by applying network calculus techniques. Both analytical and numerical results obtained in this paper indicate that our modeling and analysis well reflect the advantage of centralized network control enabled by SDN for end-to-end service provisioning; thus achieving tighter performance bound compared to traditional methods for network performance analysis.

Original languageEnglish (US)
Title of host publication2015 Symposium on Applied Computing, SAC 2015
EditorsDongwan Shin
PublisherAssociation for Computing Machinery
Number of pages6
ISBN (Electronic)9781450331968
StatePublished - Apr 13 2015
Event30th Annual ACM Symposium on Applied Computing, SAC 2015 - Salamanca, Spain
Duration: Apr 13 2015Apr 17 2015

Publication series

NameProceedings of the ACM Symposium on Applied Computing


Other30th Annual ACM Symposium on Applied Computing, SAC 2015

All Science Journal Classification (ASJC) codes

  • Software


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