Development of a novel Quality of Service and energy balancing control engine to reduce and measure the carbon emissions of distributed computing networks for high throughput computing.

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Title
Development of a novel Quality of Service and energy balancing control engine to reduce and measure the carbon emissions of distributed computing networks for high throughput computing.

CoPED ID
40cb7edd-dda3-4d94-925b-9ba6f51dd73b

Status
Active

Funder

Value
£299,481

Start Date
Sept. 30, 2022

End Date
March 31, 2024

Description

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The Charity Engine (CE) platform (ran by Worldwide Computing Company Ltd) is a grid computing solution that harnesses surplus 'idle time' computing power to provide computing services to both enterprise and academic customers worldwide to meet the high-performance computing (HPC) needs such as scientific simulations or statistical analyses. Corporate users pay for the service, while charitable or research institutions receive the excess computing power free of charge as a charitable contribution.

There is a need for a grid computing solution that reduces, measures and reports both energy requirements and subsequent carbon emissions whilst maintaining an adequate Quality of Service (QoS) to meet customer compute demands and enables corporates to fulfil CSR reporting requirements.

The aim of this project is to substantially reduce the energy consumption and CO2 emissions of the CE infrastructure by allocating tasks in a manner which minimizes the amount of energy consumed per task, while meeting the QoS constraints of the end users. The benefit will be shared with the owners of the infrastructure through reduced electricity costs and CO2 impact, and with the end users through reduced CO2 impact of their operations.

To achieve this aim, this project will exploit the technical advancements achieved by research at Cognitive Networks Limited which has designed and implemented several proof-of-concept Energy/QoS balancing control systems in several target testbeds.

The consortium will develop a robust QoS energy/balancing engine based on Reinforcement Learning that which will be integrated into the CE distributed network, to optimally select server nodes based on real-time QoS including network delay, server response time and server energy consumption.

Mark McAndrew PM_PER

Subjects by relevance
  1. Services
  2. Energy consumption (energy technology)

Extracted key phrases
  1. Robust QoS energy
  2. Grid computing solution
  3. Server energy consumption
  4. High throughput computing
  5. Computing network
  6. Energy requirement
  7. Computing service
  8. Development
  9. Novel Quality
  10. Performance computing
  11. Subsequent carbon emission
  12. Co2 emission
  13. Control engine
  14. Adequate Quality
  15. Customer compute demand

Related Pages

UKRI project entry

UK Project Locations