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QoS Enabled WiFi MAC Layer Processing as an Example of a NFV Service
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO)ORCID iD: 0000-0001-7358-8675
Karlstad University, Faculty of Economic Sciences, Communication and IT, Centre for HumanIT. Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO)ORCID iD: 0000-0002-9446-8143
2015 (English)In: Network Softwarization (NetSoft), 2015 1st IEEE Conference on, IEEE, 2015, p. 1-9Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2015. p. 1-9
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-38735DOI: 10.1109/NETSOFT.2015.7116164ISI: 000380562800045OAI: oai:DiVA.org:kau-38735DiVA, id: diva2:874714
Conference
1st IEEE Conference on Network Softwarization (NetSoft), 13-17 April 2015, London
Available from: 2015-11-27 Created: 2015-11-27 Last updated: 2019-12-12Bibliographically approved
In thesis
1. SDN-Enabled Resiliency in Computer Networks
Open this publication in new window or tab >>SDN-Enabled Resiliency in Computer Networks
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In computer networking, failures, such as breaking equipment, cable cuts, power failures and human errors continuously cause communication interruptions. Such failures may result in dissatisfied customers, loss of product reputation, violation of SLAs and even critical failures in industrial systems. SDN, which logically centralizes the control plane, is an emerging technology in computer networking. The global view provided by the SDN controller can be used to reconfigure the network in case of a link failure. However, this reconfiguration may take too long for high availability networks. With the introduction of proactive link repair, backup paths are preinstalled in the forwarding devices, reducing path recovery time.

This thesis addresses the usage of SDN to provide resiliency in high availability networks. First, we consider how SDN can be used for increasing the reliability of ICNs. Second, we investigate how similar technologies could be applied to deal with fast channel attenuation and resulting outage in mmWave backhaul networks. Finally, we look at CloudMAC-based Wireless LAN, and how SDN-enabled QoS improvements could improve connection reliability.

Abstract [en]

In computer networking, failures, such as breaking equipment, cable cuts, power failures and human errors continuously cause communication interruptions. Such failures may result in dissatisfied customers, loss of product reputation, violation of Service Level Agreements and even critical failures in industrial systems. Recently, the concept of Software Defined Networking (SDN) was introduced. SDN opens up and centralizes the control plane, which allows designing networks more resilient to failures.

In this thesis, we address the usage of SDN in order to provide resiliency in high availability networks. First, we consider how SDN enabled, proactive failure recovery can be used to provide the reliability required in Industrial Control Networks (ICNs). We also investigate how the same approach could be applied to mmWave backhaul networks to cope with fast channel attenuation and the resulting outage. Through extensive experiments, we can demonstrate an increase in reliability for both ICNs and mmWave backhaul networks. Second, we look at CloudMAC-based Wireless LAN, and how SDN-enabled traffic control algorithms could improve connection reliability. Through our experiments we can show that both discriminatory and non-discriminatory algorithms significantly increase the connection reliability. In combination, these results serve to strengthen the image of SDN as a provider of resilient, high-availability networks.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2018. p. 24
Series
Karlstad University Studies, ISSN 1403-8099 ; 2018:17
Keywords
networking, sdn, openflow, resiliency, icn, mmwave, 5g, wlan
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-66992 (URN)978-91-7063-848-0 (ISBN)978-91-7063-943-2 (ISBN)
Presentation
2018-05-11, 1B 309 Sjöström, Universitetsgatan 2, Karlstad, 10:15 (English)
Opponent
Supervisors
Available from: 2018-04-20 Created: 2018-04-12 Last updated: 2018-04-30Bibliographically approved
2. SDN-Enabled Resiliency, Monitoring and Control in Computer Networks
Open this publication in new window or tab >>SDN-Enabled Resiliency, Monitoring and Control in Computer Networks
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Next generation networks aim to increase network convergence by allowing a single network architecture to serve diverse traffic types ranging from high-bandwidth video streaming to low-latency industrial automation, while meeting their respective service level requirements. Such a converged network architecture puts high requirements on flexibility, interoperability, and resilience. While current networks exhibit some degree of network convergence, they may not reach the level of interoperability required for future application areas. This is particularly prevalent in networks that depend heavily on closed and proprietary equipment, such as industrial automation and small cell backhaul networks. Recently, Software Defined Networking (SDN) and Network Function Virtualization (NFV) have been proposed as solutions for increased network flexibility. By separating and logically centralizing the network control plane, SDN allows for dynamic control of the network infrastructure. NFV, on the other hand, enables flexibility and scalability through the virtualization and orchestration of network functions.

In this thesis, we investigate how SDN and NFV can be used to make next generation networks more reliable, flexible and programmable. We focus mainly on three areas: resiliency, monitoring, and control. First, we look at the usage of SDN to enable in-network resiliency in wireless access, backhaul and industrial automation networks. Next, we design and evaluate FastReact, a switch program that allows industrial automation networks to partially offload their distributed application logic to the data plane, reducing end to end latency and increasing network resiliency. Finally, we propose combining FastReact control with in-network telemetry event detection, significantly increasing the monitoring capacity by selectively discarding redundant telemetry information in the data plane.

Abstract [en]

Next generation computer networks aim to provide a single network architecture, which can support any type of service, ranging from high-bandwidth video streaming to low-latency industrial automation. Those services have a wide range of network requirements that must be supported by a single converged network, which puts high requirements on flexibility, interoperability, and resilience.

Recently, Software Defined Networking (SDN) and Network Function Virtualization (NFV) have been proposed as solutions for increased network flexibility. By separating and logically centralizing the network control plane, SDN allows for dynamic control of the network infrastructure. NFV, on the other hand, enables flexibility and scalability through the virtualization and orchestration of network functions.

In this thesis, we investigate how SDN and NFV can be used to make next generation networks more reliable, flexible and programmable. We focus mainly on three different areas: resiliency, monitoring, and control, and how they can be improved upon through using SDN. 

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2020. p. 39
Series
Karlstad University Studies, ISSN 1403-8099 ; 2020:2
Keywords
software defined networking, data plane programming, wireless, industrial automation, in-network telemetry, complex event processing
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-75953 (URN)978-91-7867-074-1 (ISBN)978-91-7867-075-8 (ISBN)
Public defence
2020-02-04, 1B306, Fryxellsalen, Universitetsgatan 1, KARLSTAD, 10:15 (English)
Opponent
Supervisors
Available from: 2020-01-13 Created: 2019-12-12 Last updated: 2020-02-03Bibliographically approved

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Vestin, JonathanKassler, Andreas

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