3 Year Industry-led funded PhD: Data-driven Adaptive Service Orchestration in Large-scale IoT Systems
A fully funded 3 year PhD Studentship is available to work on Adaptive Service Orchestration for Large-scale Internet of Thing (IoT) systems.
IoT services are formed by workflows orchestrated by heterogeneous sensor and application types, and are positioned to become key technologies for catalysing strategic industries for the creation of autonomous vehicles, smart homes, and healthcare. The ability to conduct IoT service orchestration at scale is still within its infancy, and faces numerous research barriers pertaining to performance, scalability, energy-efficiency, and dependability.
The aim of this project is to investigate methods for adaptive data-driven optimisation for IoT service workflows, and explore how to achieve automatic and intelligent re-orchestration of IoT systems in response to changes within their operational context (failures, energy profiles, and data traffic).
Candidates should have a 1st class degree (or equivalent) in computer science or a closely related discipline with an interest in distributed systems, web services or networking. Experience in programming languages such as Java, C# or C++ is required. Experience in web service orchestration, sensor networks, and IoT systems is an advantage, although not required.
This project will require a hands-on approach and the expectation is that a self-motivated candidate with excellent interpersonal skills will perform internationally leading research work and produce top quality publications. In addition, one of the aims of the project, informed by business problems and data analysis findings, will be the development of a prototype platform using smart buildings as a case study.
This doctoral research project will be supervised by Lancaster University and Invisible Systems. Invisible Systems, now within its 14th year, is a Cumbrian based software & electronics design manufacturing company that focuses on energy saving, compliance and asset management via robust rf wireless monitoring and energy savings solutions with their bespoke software programme (Realtime-Online™). Invisible Systems enable customers to operate their building, process or assets, in an environmentally friendly way; providing visibility of site(s) operational consumption, compliance and process efficiency, highlighting where energy use can be reduced, systems are failing, have operated, in real-time, so processes can be improved and costs can be saved. Invisible Systems works with clients across the UK including National Grid, NPower, British Gas, United Utilities, Network Rail among others.
Why Lancaster University?
Lancaster University is ranked among the top ten universities in the UK. We have invested over £450m into our campus in the last ten years, including our new Engineering building, the refurbishment of the Library, Physics and Chemistry facilities and a £20m sports centre and facilities, with a further £135m investment planned.
We’re great for nurturing talent and links with industry; we’ve over 5000 successful partnerships with businesses. We’re global, with a huge number of research links around the world which provide exciting opportunities for our students, and we’re collegiate, providing you with a supportive student environment.
To apply for this opportunity please apply by email to firstname.lastname@example.org with the subject “Data-driven Adaptive Service Orchestration in Large-scale IoT Systems” and include:
Closing date: 3rd October 2017
School of Computing and Communications
The School of Computing and Communications, ranked 12th amongst the computer science departments in the UK (REF 2014), and delivers postgraduate taught programmes in the disciplines of computer science, communication systems, data science and cyber security. Our ethos is to combine research excellence with practical, experimental approaches to equip you with the knowledge and skills to achieve your career aspirations.
Our students benefit from high quality teaching from internationally leading academics, and from state-of-the-art services and facilities including dedicated teaching laboratories, individual supervision, and mentoring by a member of academic staff. This post is offered through the Cumbrian Innovations Platform and funded by the European Regional Development Fund.
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