University of Oxford Featured PhD Programmes
University of Leeds Featured PhD Programmes
Centre for Genomic Regulation (CRG) Featured PhD Programmes

Adaptive Service Composition Techniques and Algorithms for Internet of Things (Self-Funded Students Only)


Cardiff School of Computer Science & Informatics

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
Prof O F Rana , Dr C Perera Applications accepted all year round Self-Funded PhD Students Only

About the Project

Service composition is a collection of services where, many smaller services are combined together to a larger service. Service composition is the problem of aggregating services in such a way that given (functional and not functional) requirements are satisfied. Typically, Web service composition is represented by a plan consisting of tasks that, at run-time, are instantiated to the actual services satisfying users’ requirements. Due to the increasing number of services available offering similar functionalities, it is hard for users to select an optimal service composition among a list of candidate services that satisfy their needs.

Service composition is comparatively old research area within computer science. Most of the early work has been done by the web services community specially focusing web service composition domain. Most popular web services composition problem is Travel Planning problem. Over the years, many researchers have proposed many different techniques to address the problem.

Let us now look at this problem from Internet of Things (IoT) point of view. Internet of Things is a network of devices (including sensors). The devices are heterogeneous and varies from each other significantly. Ideal vision (at least most of the time) is to develop IoT applications with the help of already deployed devices. Each of the devices may have different capabilities therefore may only capable of running certain type of devices.

For example, a particular IoT application may need to compose certain type of devices together to accomplish its end goal. Further, due to heterogeneity and constraints, certain services may only be able to run on certain device. Form abstract point of view, this is a very similar to the problem we have dealt in web services domain. We believe that IoT can be greatly benefitted by the techniques developed by webservices composition community and other similar communities.

IoT is a applied domain where the community composed from research scientist to software developers to hobbyist to teenager who may tinkering IoT application. As most of the work related web services composition is done by research community, knowledge seems to be stuck within the research community where it is different for developers to use the techniques developed in service composition domain. This PhD project focused on developing novel service composition techniques for Internet of Things

HOW TO APPLY

Applicants should apply to the Doctor of Philosophy in Computer Science and Informatics.

In the research proposal section of your application, please specify the project title and supervisors of this project and copy the project description in the text box provided. In the funding section, please select the ’self -funding’ option and specify that you are applying for the Adaptive Service Composition Techniques and Algorithms for Internet of Things project.

Please contact Dr. Charith Perera ([Email Address Removed]) to discuss this project.
Supervisor Profile: http://charithperera.net/

Funding Notes

Self-Funded Students Only

ELIGIBILITY CRITERIA
A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject.
Applicants for whom English is not their first language must demonstrate their proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component.
Search Suggestions

Search Suggestions

Based on your current searches we recommend the following search filters.



FindAPhD. Copyright 2005-2020
All rights reserved.