Software Defined Networking (SDN) Technologies

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  • Competition Funded Project (Students Worldwide)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Project description

With the evolution of networks from IPv4 to future Internet of Things and IPv6 replacing IPv4 at some point soon there has been increasing interest in making the network stacks on our various devices more adaptable to the range of applications the network is used for. In particular, wireless sensor network devices and other power constrained systems will need their network stacks to be optimized to perhaps maximise throughput of core data, or of real-time triggers or other data types. The internet stack consists today of a large set of more heavily coupled protocols than is desirable. This coupling of protocols plus the infrastructure tendency to treat all traffic as either best effort or prioritized to the needs of large high paying customers means that building different or bespoke network stacks specialized for a small range of applications does not happen as it for example, too expensive and risky to contemplate.

Experiments with ad-hoc networks and sensor networks has lead to the development of many more protocols designed for particular scenarios which often have a narrow peak performance range which is very application and traffic dependent. If anything changes in the pattern of traffic then the network performance will drop. Therefore, adaptive techniques that will change the network configuration to match the current topology and traffic patterns will soon become desirable. In all likelihood these will be based on cognitive technologies, machine learning and other Artificial Intelligence methods.

Future network stacks will either be hand coded by an elite of programmers or machine generated. In order to machine generate software a machine needs to have a great deal of knowledge across quite a wide range of domains. Capturing and transforming this knowledge into runnable code is challenging. Ensuring the generated code is secure and bug free is also challenging.

I'm interested to talk to anybody who is interested in investigating the possibilities to move from static network stacks to more dynamic ones as part of PhD level research. In terms of applications for these technologies my main interests are in ad-hoc and low power sensor/thing networks (Internet of Things IoT) but I'm also interested in gateways between different networks and the configuration and management of infrastructure networks.

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