Embedded Energy Management System (EEMS)
Lead Participant:
SEAGATE SYSTEMS (UK) LIMITED
Abstract
This feasibility study is looking at energy efficiency in data centres. Our work will consist of two phases. The first will use data science and AI techniques to accurately extract useful information to model how the data centre uses energy.
The second phase will learn the impact of high energy events in the data centre and issue commands to reduce energy usage by rescheduling certain parts of data flow.
Not only will this minimise energy usage but it will also maximise reliability and performance.
The second phase will learn the impact of high energy events in the data centre and issue commands to reduce energy usage by rescheduling certain parts of data flow.
Not only will this minimise energy usage but it will also maximise reliability and performance.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| SEAGATE SYSTEMS (UK) LIMITED | £88,755 | £ 56,553 |
Participant |
||
| UNIVERSITY OF PORTSMOUTH | £41,979 | £ 41,978 |
People |
ORCID iD |