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.

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.