Scalable and Self-x optical technologies for next generation data centres
Lead Research Organisation:
University College London
Department Name: Electronic and Electrical Engineering
Abstract
Data Centres of different sizes form the backbone of the Cloud, Edge and Mobile Computing. They shape the digital infrastructure for next generation applications and services across Internet of Things, 5G, artificial intelligence, virtual and augmented reality as well as Tactile Internet among others.
The PhD project will investigate optical technologies, systems and networks to support next generation Data Centres. Of particular focus and interest to be explored are elements on scalable optical switching fabrics (from single switches to reconfigurable topologies) to support 1000s of optical channels (by looking into ultra-wideband wavelength division multiplexing as well as space division multiplexing) and expanding to accommodate millions of end points (servers, disaggregated compute/memory/accelerators). For example, the integration of advanced optical and signal monitoring capabilities into optical switch fabrics will be investigated. Machine-learning methods and algorithms will be explored to deliver dynamic self-x (configuring, monitoring, planning, learning, repairing and optimising) systems and networks.
The activities will be supervised by Dr. George Zervas (University College London), as well as Dr. Michael Enrico (HUBER+SUHNER Polatis).
Relevance to EPSRC thematic areas - ICT Networks and Distributed Systems, Artificial Intelligence, Optical Communications
The PhD project will investigate optical technologies, systems and networks to support next generation Data Centres. Of particular focus and interest to be explored are elements on scalable optical switching fabrics (from single switches to reconfigurable topologies) to support 1000s of optical channels (by looking into ultra-wideband wavelength division multiplexing as well as space division multiplexing) and expanding to accommodate millions of end points (servers, disaggregated compute/memory/accelerators). For example, the integration of advanced optical and signal monitoring capabilities into optical switch fabrics will be investigated. Machine-learning methods and algorithms will be explored to deliver dynamic self-x (configuring, monitoring, planning, learning, repairing and optimising) systems and networks.
The activities will be supervised by Dr. George Zervas (University College London), as well as Dr. Michael Enrico (HUBER+SUHNER Polatis).
Relevance to EPSRC thematic areas - ICT Networks and Distributed Systems, Artificial Intelligence, Optical Communications
People |
ORCID iD |
| Georgios Zervas (Primary Supervisor) | |
| Zacharaya Shabka (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/R513143/1 | 01/10/2018 | 30/09/2023 | |||
| 2257981 | Studentship | EP/R513143/1 | 01/10/2018 | 30/03/2023 | Zacharaya Shabka |