A Novel Machine Learning-Driven Edge Computing

The development of Edge Computing (EC) has been evolving under the umbrella of cloud computing where resources are centralized and managed in data centers. However, the limitation of cloud-centric service architecture stands out when it comes to service delivery at the network edge such as Internet of Things (IoT) scenarios, where a plethora of devices are involved and the real-time requirement of applications really matters. Driven by the demand of time-sensitive and dataintensive applications, EC has attracted wide attention as one of the cornerstones for modern service architectures. An edge-based system involves comprehensive aspects whilst at the core of the paradigm are the optimization problems concerning the way computation, communication, and caching are performed.

Machine Learning (ML) schemes, have shown great potential in combining powerful decision-making and high-dimensional analysis capability to facilitate a highly intelligent edge system. In this project, the candidate will explore the current state of the art of EC paradigms and the ML-based solutions. Then, the candidate will develop a new approach to challenge the current limits under the context of these key pillars: task offloading, resource allocation and caching strategy in EC. The proposed solutions should overcome the performance of existing works in terms of different key performance metrics. 

Academic qualifications

A first-class honours degree, or a distinction at master level, or equivalent achievements in Computer Science-related area with a good fundamental knowledge of computer science and cloud Computing.

English language requirement

If your first language is not English, comply with the University requirements for research degree programmes in terms of English language.

Application process

Prospective applicants are encouraged to contact the supervisor, Professor Ahmed Al-Dubai (A.Al[Email Address Removed]) to discuss the content of the project and the fit with their qualifications and skills before preparing an application. 

The application must include: 

Research project outline of 2 pages (list of references excluded). The outline may provide details about

• Background and motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
• Research questions or
• Methodology: types of data to be used, approach to data collection, and data analysis methods.
• List of references

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Recent and complete curriculum vitae. The curriculum must include a declaration regarding the English language qualifications of the candidate.
• Supporting documents will have to be submitted by successful candidates.
• Two academic references (but if you have been out of education for more than three years, you may submit one academic and one professional reference), on the form can be downloaded here.

Applications can be submitted here.

Download a copy of the project details here.