Policy-based QoS management framework for software-defined networks
Conference paper
Al-Jawad, A., Shah, P., Gemikonakli, O. and Trestian, R. 2018. Policy-based QoS management framework for software-defined networks. ISNCC 2018: International Symposium on Networks, Computers and Communications. Rome, Italy 19 - 21 Jun 2018 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ISNCC.2018.8530994
Type | Conference paper |
---|---|
Title | Policy-based QoS management framework for software-defined networks |
Authors | Al-Jawad, A., Shah, P., Gemikonakli, O. and Trestian, R. |
Abstract | With the emerging trends of virtualization of cloud computing and big data applications, network management has become a challenging problem for optimizing the network state while satisfying the applications’ Quality of Service (QoS) requirements. This paper proposes a policy-based management framework over Software-Defined Networks (SDN) for QoS provisioning. The proposed approach monitors the QoS parameters of the active flows and dynamically enforces new decisions on the underlying SDN switches to adapt the network state to the current demanded high-level policies. Moreover, the proposed solution makes use of Neural Networks to identify the violating flows causing the network congestion. Upon detection of a policy violation two route management techniques are implemented, such as: rerouting and rate limiting. The proposed framework was implemented and evaluated within an experimental test bed setup. The results indicate that the proposed PBNM-based SDN framework enables QoS provisioning and outperforms the default SDN in terms of throughput, packet loss rate and latency. |
Keywords | SDN; Policy-Based Network Management; QoS; Neural Network |
Conference | ISNCC 2018: International Symposium on Networks, Computers and Communications |
Proceedings Title | 2018 International Symposium on Networks, Computers and Communications (ISNCC) |
Series | International Symposium on Networks Computers and Communications |
ISSN | 2472-4386 |
ISBN | |
Electronic | 9781538637791 |
Electronic | 9781538637784 |
Paperback | 9781538637807 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Publication dates | |
19 Jun 2018 | |
Online | 11 Nov 2018 |
Publication process dates | |
Deposited | 30 Apr 2018 |
Accepted | 01 Apr 2018 |
Output status | Published |
Accepted author manuscript | File Access Level Open |
Copyright Statement | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ISNCC.2018.8530994 |
Scopus EID | 2-s2.0-85058446551 |
Web of Science identifier | WOS:000494708800059 |
Web address (URL) of conference proceedings | https://ieeexplore.ieee.org/xpl/conhome/8511028/proceeding |
Related Output | |
Has metadata | http://www.scopus.com/inward/record.url?eid=2-s2.0-85058446551&partnerID=MN8TOARS |
Language | English |
https://repository.mdx.ac.uk/item/87q0x
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