Fog computing can support Web services with fast response time and low bandwidth usage by moving computation from the Cloud to machines that are located close/on the Edge (i.e., close/at the end-users’ devices). The existing fog computing frameworks support the design and the deployment of services that are deployed/bound to specific machines on the Edge. In this case, service developers should statically define/decide at the development time of their software what services should be deployed on what type of machines on the Edge. However, services may not be able to run on machines on the Edge that are usually resource constrained. The performance of services depends not only on their particular development details but also on their particular runtime use (e.g., dependence on the exchanged data) that cannot be known at the development time of the services. Thus, the project faces the challenge of redesigning/designing service-oriented software at runtime to make it deployable on the Edge.
Project Description:
To address the challenge of runtime deployment decisions, the project focuses on the programming model of the Function-as-a-Service (FaaS) in serverless computing. The FaaS model is suitable for Fog computing because it is based on nanoservices. Nanoservices are very light-weight (micro)services whose programming interfaces provide a very small number of functions. Nanoservices can be executed on resource-constrained machines on the Edge. The FaaS model is suitable for composing nanoservices, given that the software built by developers is usually composed of multiple services.
However, developers do not necessarily build services that are nanoservices and especially, the built services are not necessarily deployable on the Edge. Moreover, the nanoservice composition should be dynamic in order to address the challenge of runtime deployment decisions. In particular, alternative nanoservices deployed on various machines on the Edge should be dynamically selected depending on the exchanged data and the used machines. The alternative nanoservices should provide the same functionality to each other so they can be interchangeably used by the service-oriented software built by developers. In other words, the dynamic data-oriented (i.e., based on the exchanged data) composition of nanoservices is required.
Overall, the project proposes automatic mechanisms that design/redesign existing service-oriented software into nanoservices. The produced nanoservices are designed in such a way that follow the FaaS model of serverless computing. Moreover, the project involves mechanisms that dynamically compose/recompose nanoservices depending on the exchanged data and the used machines on the Edge.
Project Key Words: Fog/Edge computing, nanoservices, serverless computing.
Start Date: 01/10/22
Application Closing date: 28/02/22
For further information about eligibility criteria please refer to the DfE Postgraduate Studentship Terms and Conditions 2021-22 at https://go.qub.ac.uk/dfeterms
Applicants should apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/
Academic Requirements:
A minimum 2.1 honours degree or equivalent in Computer Science, Software Engineering or relevant degree is required.
Funding Notes:
This three year studentship, for full-time PhD study, is potentially funded by the Department for the Economy (DfE) and commences on 1 October 2022. For UK domiciled students the value of an award includes the cost of approved tuition fees as well as maintenance support (Fees £4,500 pa and Stipend rate £15,609 pa - 2022-23 rates to be confirmed). To be considered eligible for a full DfE studentship award you must have been ordinarily resident in the United Kingdom for the full three year period before the first day of the first academic year of the course.
For candidates who do not meet the above residency requirements, a small number of international studentships may be available from the School. These are expected to be highly competitive, and a selection process will determine the strongest candidates across a range of School projects, who may then be offered funding for their chosen project.
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