Yali is investigating Service Level Agreement (SLA) based resource scheduling for big data analytics in cloud computing environments.
Analysing big data can have benefits in decision-making and problem-solving in many different domains of life, from science and engineering, to medicine, commerce and more.
Cloud computing is a suitable platform for Big Data Analytic Applications (BDAAs), which can reduce application cost considerably, by elastically provisioning resources based on user requirements and in a pay as you go model. BDAAs are typically used by large enterprises, are expensive, and are usually catered for specific domains. In addition, they require large-scale computing and their resource requirements fluctuate over time.
Yali’s research is looking at how to encourage and benefit users in a variety of application domains to make use of big data analytics as consumable services – to access data analytics easily and at lower price and with SLA guarantees via a general Analytics-as-a-Service (AaaS) platform.
“To support the AaaS platform, my research focuses on efficiently and dynamically scheduling Cloud resources for BDAAs, which not only satisfies Quality of Service (QoS) requirements of data analytical requests as guaranteed in SLAs, but also maximizes the profit for AaaS providers by offering cost-effective resource scheduling solutions,” Yali says.
The Anita Borg Scholarship has been established by Google to honour the memory of Dr Anita Borg and to support women in technology. Dr Borg devoted her adult life to revolutionising the way we think about technology and removing the barriers that keep women and minorities from entering computing and technology fields.