Policy-based QoS management framework for software-defined networks

Al-Jawad, Ahmed, Shah, Purav, Gemikonakli, Orhan and Trestian, Ramona (2018) Policy-based QoS management framework for software-defined networks. In: IEEE International Symposium on Networks, Computers and Communications, 19-21 June 2018, Rome, Italy. (Accepted/In press)

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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.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 24194
Notes on copyright: © 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.
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Depositing User: Ramona Trestian
Date Deposited: 30 Apr 2018 11:00
Last Modified: 05 Apr 2019 01:09
URI: https://eprints.mdx.ac.uk/id/eprint/24194

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