Award details

Data-Driven Mobile Networking Techniques for Efficient QoS Provisioning Ref: 3148

About the award

Details

Recent years have witnessed the rapid proliferation of mobile devices such as smart phones and wearable devices, which are equipped with various built-in sensors and possess powerful computing and communications capabilities. The large number and diverse advanced functionalities of mobile devices empower ordinary citizens to contribute heterogeneous and cross-space data including machine-sensed data from mobile devices (physical space) and user-generated data from mobile social networking (cyber space), which are aggregated and fused in the cloud for knowledge discovery and service delivery. The explosive growing of data traffic in mobile networks poses imminent challenges while opening up new opportunities to all the aspects of the wireless and mobile system design, such as bandwidth efficiency, computing performance and network capacity. In this project, we will investigate two emerging open problems facing networking system and protocol design:

1) How to design a scalable mobile network architecture for efficient handling and robust delivery of ever-growing data traffic?

2) How to effectively learn from cross-space data to improve the Quality-of-Service (QoS) performance of mobile networking system? To answer these problems, this project will propose novel data-driven networking architectures and solutions for efficient QoS provisioning over wireless mobile networks.


This project aims to design and develop novel data-driven networking architectures and solutions for efficient QoS provisioning over wireless mobile networks. In outline, the proposed project intends to


* Design a Software-Defined Networking (SDN) based network resource management framework where the packet routing and content caching decisions are jointly optimized.


* Develop an innovative learning-based distributed Information-Centric Networking (ICN) caching scheme to leverage the insights on the characteristics and popularity of contents, the preference and QoS demand of users, and the traffic and link conditions.


* Develop and validate a comprehensive mathematical model for evaluating the performance of the proposed resource management and caching techniques with multimedia applications and heterogeneous network conditions.
The project seeks to harness the complementary features of SDN and ICN to fully unlock their potential capabilities and remedy the intrinsic deficiencies of each other. To improve the network QoS performance, an innovative learning based ICN caching strategy will be proposed to leverage the insights on the characteristics and popularity of contents, the preference and QoS demand, and the traffic and link conditions. In order to investigate the QoS of the proposed schemes, a mathematical model will be developed and validated by computer simulation/emulation.


This award provides annual funding to cover UK/EU tuition fees and a tax-free stipend.  For students who pay UK/EU tuition fees the award will cover the tuition fees in full. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee.


The studentship will be awarded on the basis of merit for 3.5 years of full-time study to commence in Sep 2018 and is subject to confirmation of funding.

Entry requirements

Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. 


If English is not your first language you will need to have achieved at least 6.0 in IELTS and no less than 6.0 in any section by the start of the project.  Alternative tests may be acceptable (see http://www.exeter.ac.uk/postgraduate/apply/english/).

How to apply

In the application process you will be asked to upload several documents. 


• CV
• Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project).
• Research proposal
• Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying)
• Names of two referees familiar with your academic work. You are not required to obtain references yourself. We will request references directly from your referees if you are shortlisted.
• If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English


The closing date for applications is midnight on 1 June 2018.  Interviews will be held on the University of Exeter Streatham Campus the week commencing 28 May 2018.

Summary

Application deadline:1st June 2018
Value:£14,777 for 3.5 years
Duration of award:per year
Contact: EMPS PGR Team +44 (0) 1392 722730 emps-pgr-ad@exeter.ac.uk