Project
EDGELESS, European Union’s Horizon Europe research and innovation programme. - 101092950, €5.42 million
Role: Research Associate
University of Cambridge
(Feb 2024 - Present) EDGELESS project aims to leverage the serverless concept in all the layers in the edge-cloud continuum to fully benefit from diverse and decentralised computational resources available on-demand close to where data are produced or consumed. In particular, we aim at realising an efficient and transparent horizontal pooling of the resources on edge nodes with constrained capabilities or specialised hardware, smoothly integrated with cloud resources, which is a giant leap forward compared to state-of-the-art vertical offloading solutions where the edge is a mere supplement of the cloud.
Internet of Digital Twin Things, Innovate UK, €2.68 million
Role: Research Associate (Lead)
Current digital twin practices have limitations due to the central location of most digital twin models, which can cause data processing latency and network bandwidth issues. Additionally, the use of proprietary digital twin solutions can create technology silos and compatibility issues when interfacing virtual subsystems from different manufacturers. To address these issues, we propose a novel digital twin framework called the Internet of Digital Twin Things (IoDT2). This framework will allow for the easy sharing of models and data across networks, and computation resources can dynamically be formed to execute simulations. Each model can be instantiated at edge, fog, or cloud level where it exchanges data with other models, performs simulations, and returns results. This will enable practitioners to focus on creating necessary core models for their systems instead of being bogged down by complex software configuration. The proposed framework will be built on an Information Centric Network (ICN) inspired digital twin network called Digital Twin Centric Network (DTCN), which will allow digital twin models, data, and compute resources to be published and located across networks easily. The authors believe that this framework will have applications in various industries, such as manufacturing (Industry 4.0), healthcare, and smart cities. To demonstrate and validate the framework, the authors will define and develop use three use cases spanning across construction, earthquake and smart transport. This will involve splitting digital twin models into meaningful components and moving a subset of these components to the edge to improve latency and bandwidth. The IoDT2 framework will simply take specified digital twin models, run simulations, and return simulation results.
Smart Manufacturing Data Hub, Innovate UK, £50 million
Role: Research Associate
(Nov 2022- Feb 2024) The £50 million Smart Manufacturing Data Hub (SMDH) will support small and medium size manufacturers to capture and better utilise their data, helping them increase productivity, growth and sustainability. Businesses in sectors spanning from food and drink, aerospace and many more will be supported to develop, test and adopt the latest data-driven technologies. Nearly 10,000 manufacturers are expected to benefit from the hub and 13,000 jobs will be supported, helping to boost economic growth and level-up regions across the UK. The hub will be supported by £20 million from the UK government backed Made Smarter Innovation Programme, along with £30 million of business co-investment.
Serverless Edge Computing for 5G Edge Devices, Innovate UK, £499,223
Role: Research Associate （Lead）
</p>Edge devices require high-quality internet connections as alerts/detections need to be processed in real-time to enable effective action to minimise the impact of health&safety issues. On construction sites and other industrial environments, the lack of reliable connectivity is the main barrier to adoption. Construction firms also need to ensure that personal data is protected. Existing cloud-based solutions for edge computing require complex set-up and configuration, create potential data security issues, and are not dynamic enough to facilitate real-time data processing and achieve required latency(5ms). EMS and Loughborough University are developing a novel serverless edge FaaS (Function as a Service) engine(ServerlessEdge) to optimise existing i-MO routers to enable connected edge devices to operate onsite in real-time in traditionally low connectivity environments without the need to deploy and support additional on-site IT infrastructure or centralised services. </p>
Intelligent Edge of Things, Innovate UK, £972,750
Role: Research Assistant （Lead）
(Nov 2021-2022 June) This project takes the concept of edge computing to a new level by introducing the third, local, tier in addition to the data centre and edge computing tiers. We utilise Artificial Intelligence to unleash the full potential of each Edge architectural tier to meet different application requirements. This project focuses on developing an intelligent three-tier Edge IoT architecture for enabling novel services around business areas such as smart transportation, Industry 4.0 and entertainment. We incorporate VPN and Kubernetes to build an edge computing platform across multiple networks. Computing resources, located in different network providers' domains, are efficiently federated and hence brings a variety of opportunities in the sense of edge clouds federation. This project is sponsored by Innovate UK.