Arun Adiththan of General Motors

A common trend among many businesses in the last decade is the use of cloud-based computing services. The disparate business and administrative practices adopted by cloud service providers such as Amazon (AWS), Google Cloud, and Microsoft (Azure) impact the quality, trust, and performance experienced by customer applications. A concrete insight into the non-functional properties of a cloud service helps customers to choose a provider that best fits their needs and providers to identify improvements needed in their provisioning strategies.

This talk will describe a model-based system identification technique for quality assessment of cloud services. We shall see how the design of a cloud-based system – the algorithmic and workflow processes – can be inferred from service-level quality attributes such as availability, elasticity, and agility. The assessment module involves computational model of the system under test, collection and analysis of quality related service metadata, and system testing and inference techniques. The assessment method will be discussed using a cloud-based content distribution network (CDN) case study.

Biography:

Arun Adiththan is a Researcher at General Motors R&D, Warren, MI. In his research on complex software systems verification and validation, he uses methods and tools such as model-based systems engineering, simulation and data analysis. Arun earned his Ph.D. in Computer Science from City University of New York in 2018. Prior to that, he received a Master’s and Bachelor’s in Computer Science and Engineering from Anna University, India. He has published more than 25 international conference and journal papers.

Address:Location is TBD, , Rochester, Michigan, United States, 48306