报告题目：Prescriptive Analytics for Energy Efficient Datacentres
报 告 人：Dr John Panneerselvam
报告地点：安徽大学磬苑校区理科D楼108会议室
报告时间：2018年12月21日 周五 15：00
报告摘要：Given the evolution of Cloud Computing in recent years, users and clients adopting Cloud Computing for both personal and business needs have increased at an unprecedented scale. This has naturally led to the increased deployments and implementations of Cloud datacentres across the globe. As a consequence of this increasing adoption of Cloud Computing, Cloud datacentres are witnessed to be massive energy consumers and environmental polluters. Whilst the energy implications of Cloud datacentres are being addressed from various research perspectives, predicting the future trend and behaviours of workloads at the datacentres thereby reducing the active server resources is one particular dimension of green computing gaining the interests of researchers and Cloud providers. However, this includes various practical and analytical challenges imposed by the increased dynamism of Cloud systems. The behavioural characteristics of Cloud workloads and users are still not perfectly clear which restrains the reliability of the prediction accuracy of existing research works in this context. To this end, this talk presents our descriptive analytics that uncovers the hidden caused of excess energy expenditures in datacentre execution along with our developed novel resource optimisation framework that aims to avail the most optimum level of resources for executing jobs with reduced server energy expenditures and job terminations. This optimisation framework encompasses a resource estimation module to predict the anticipated resource consumption level for the arrived jobs and a classification module to classify tasks based on their resource intensiveness.
主办单位：安徽大学计算机科学与技术学院
欢迎各位老师，同学届时前往！
科学技术处
2018年12月20日