Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
In-Network Caching and Control for Industrial Automation Publish/Subscribe Networks
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-7358-8675
(English)Manuscript (preprint) (Other academic)
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-76287OAI: oai:DiVA.org:kau-76287DiVA, id: diva2:1385133
Available from: 2020-01-13 Created: 2020-01-13 Last updated: 2020-01-13Bibliographically approved
In thesis
1. 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

Open Access in DiVA

No full text in DiVA

Authority records BETA

Vestin, Jonathan

Search in DiVA

By author/editor
Vestin, Jonathan
By organisation
Department of Mathematics and Computer Science (from 2013)
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 22 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf