Latency-based graph selection manager for end-to-end network service on heterogeneous infrastructures

Changwoo Kim, Yujeong Oh, Jaiyong Lee

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

Abstract

As Network Functions Virtualization (NFV) / Software Defined Networking (SDN) technologies gradually mature as representative next-generation network technologies, management and orchestration (MANO) technologies that manage the Service Function Chain (SFC) have received plenty of attention from industry and academia. However, a number of present research challenges have been addressing only resource efficiency related with usage rates of Virtualized Network Functions (VNFs) without network properties in terms of NFV-MANO orchestrator. Different network characteristics are considered due to use network slicing technology which provides dedicated logical networks from a physical network for tailored network services. In this paper, we proposed Graph Selection Manager (GSM) to provide one or more VNF forwarding graphs under maximum latency considering inter-latency and intra-latency as well as VNFs and network capacity. As a result of experimental emulation, we found one or more VNF forwarding graphs meeting service level agreement (SLA) of a tenant in limited network capacity, and established one or more end-to-end network services with sustained low latency.

Original languageEnglish
Title of host publication32nd International Conference on Information Networking, ICOIN 2018
PublisherIEEE Computer Society
Pages534-539
Number of pages6
ISBN (Electronic)9781538622896
DOIs
Publication statusPublished - 2018 Apr 19
Event32nd International Conference on Information Networking, ICOIN 2018 - Chiang Mai, Thailand
Duration: 2018 Jan 102018 Jan 12

Publication series

NameInternational Conference on Information Networking
Volume2018-January
ISSN (Print)1976-7684

Conference

Conference32nd International Conference on Information Networking, ICOIN 2018
CountryThailand
CityChiang Mai
Period18/1/1018/1/12

Fingerprint

Managers
Next generation networks
Industry
Network function virtualization

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

Cite this

Kim, C., Oh, Y., & Lee, J. (2018). Latency-based graph selection manager for end-to-end network service on heterogeneous infrastructures. In 32nd International Conference on Information Networking, ICOIN 2018 (pp. 534-539). (International Conference on Information Networking; Vol. 2018-January). IEEE Computer Society. https://doi.org/10.1109/ICOIN.2018.8343176
Kim, Changwoo ; Oh, Yujeong ; Lee, Jaiyong. / Latency-based graph selection manager for end-to-end network service on heterogeneous infrastructures. 32nd International Conference on Information Networking, ICOIN 2018. IEEE Computer Society, 2018. pp. 534-539 (International Conference on Information Networking).
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Kim, C, Oh, Y & Lee, J 2018, Latency-based graph selection manager for end-to-end network service on heterogeneous infrastructures. in 32nd International Conference on Information Networking, ICOIN 2018. International Conference on Information Networking, vol. 2018-January, IEEE Computer Society, pp. 534-539, 32nd International Conference on Information Networking, ICOIN 2018, Chiang Mai, Thailand, 18/1/10. https://doi.org/10.1109/ICOIN.2018.8343176

Latency-based graph selection manager for end-to-end network service on heterogeneous infrastructures. / Kim, Changwoo; Oh, Yujeong; Lee, Jaiyong.

32nd International Conference on Information Networking, ICOIN 2018. IEEE Computer Society, 2018. p. 534-539 (International Conference on Information Networking; Vol. 2018-January).

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

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Kim C, Oh Y, Lee J. Latency-based graph selection manager for end-to-end network service on heterogeneous infrastructures. In 32nd International Conference on Information Networking, ICOIN 2018. IEEE Computer Society. 2018. p. 534-539. (International Conference on Information Networking). https://doi.org/10.1109/ICOIN.2018.8343176