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  • 2019FawcettPhD

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Scalable and responsive SDN monitoring and remediation for the Cloud-to-Fog continuum

Research output: ThesisDoctoral Thesis

Published
Publication date26/09/2019
Number of pages220
QualificationPhD
Awarding Institution
Supervisors/Advisors
Award date2/07/2019
Publisher
  • Lancaster University
Original languageEnglish

Abstract

Since the inception of the digital era the sharing of information has been revolutionary to the way we live, inspiring the continuous evolution of computer networks. Year by year, humankind becomes increasingly dependent on the use of connected services as new technologies evolve and become more widely accessible. As the widespread deployment of the Internet of Things, 5G, and connected cars rapidly approaches, with tens of billions of new devices connect- ing to the Internet, there will be a plethora of new faults and attacks that will require the need to be tracked and managed. This enormous increase on Internet reliance which is stretching the limits of current solutions to network monitoring introduces security concerns, as well as challenges of scale in operation and management. Todays conventional network monitoring and management lacks the flexibility, visibility, and intelligence required to effectively operate the next generation of the Internet. The advent of network softwarisation provides new methods for network management and operation, opening new solutions to net- work monitoring and remediation. In parallel, the increase in maturity of Edge computing lends itself to new solutions for scaling network softwarisation, by deploying services throughout the network.
In this thesis, two proof-of-concept systems are presented which together harness the use of Software Defined Networking, Network Functions Virtualisation, and Cloud-to-Fog computing to address challenges of scale and network security: Siren is an open platform which manages the resources within the Internet, bridging network and infrastructure management and orchestration.

Tennison is a network monitoring and remediation framework which tackles monitoring scalability through adapting to network context and providing a suitable architecture to the network topology, including the use of centralised, distributed, and hierarchical deployments.