Intelligent Policy Conflict Resolution in Multi-Domain SDNFV
Software Defined Networking (SDN) and Network Functions Virtualization (NFV) are emerging technologies in the fields of telecommunications and networking. In combination, SDNFV introduces a programmable, dynamic, and flexible network topology. To date, security solutions have been predominantly proposed either for SDN or for NFV separately and only to a limited extent for the combined SDNFV environment. The deployment of SDNFV in multitenant, multi-domain environments requires an integrated approach to security.
In the multi-tenant, multi-domain network, applications from different vendors/operators will use shared resources to deliver a specific function. In this environment, conflicts arise between policies from different applications (network functions). Permissions-based solutions have been proposed to control access to the shared resources. However, these solutions do not resolve the conflict between the competing policies. The main goal of this PhD thesis is to investigate methods and propose and design a method to enable efficient and effective policy conflict resolution between applications in a multi-domain SDNFV environment.
- To investigate state-of-the-art policy conflict resolution techniques for multiple applications in a SDNFV environment.
- To study new methods for detecting and resolving conflicts from multiple vendor applications.
- To propose a framework for network policy conflict resolution in a multi-domain SDNFV environment.
- To design and develop the language and tools required to demonstrate the proposed PCR framework.
Students entering the programme will normally be required to have a 2.1 BSc/BEng in Computer Science, Electrical and Electronic Engineering, or a maths based engineering or physical science degree, or equivalent qualification recognised by the University.
Students holding an appropriate MEng or MSc (Software conversion) will normally be required to have a 2.1 or commendation (distinction) respectively. Furthermore, additional criteria may be applied. All applicants must have significant mathematical and programming experience.
How to Apply:
Applicants should apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/
Supervisor Name: Dr. Sandra Scott-Hayward
Tel: +44 (0)28 9097 1898