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Engineering Self-Adaptive Software Systems - Dr. Hamzeh Khazaei

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  • Fri, 05/05/2017 - 10:00am - 11:00am

Nowadays more and more software systems take advantage of the flexible environment offered by the cloud to provide enhanced services in a timely manner. However, as applications offer more advanced features, the complexity of the software development life cycle grows in parallel; big data and IoT applications are prime examples of such software systems. Therefore, engineering such complex and distributed software systems requires a specific set of design patterns and best practices during development, deployment and runtime operation. Optimized configuration and runtime operation have been realized to be the most challenging part in the life cycle of large scale systems. Due to sheer scale and complexity of such systems coupled with volatile nature of the cloud, manual management is no longer an option. Therefore, autonomic management systems are required to provide self-* capabilities—including but not limited to self-optimization, self-configuration, self-protection and self-healing—for distributed cloud applications and platforms. Autonomic managers continuously monitor the application at runtime, analyze, plan and execute corrective actions in case of internal changes or external stimuli.

This talk describes engineering model-based autonomic management systems for distributed cloud applications. To this end, I will first talk about my work on performance modeling of cloud computing centers. More specifically, challenges of building performance models with high level of fidelity and tractability will be discussed. Second, I will explain how analytical performance models can be leveraged to build autonomic managers for big data software systems. Third, the coordination among multiple autonomic management systems will be discussed in the context of layered IoT applications.  In the end, I will describe and demonstrate the connected vehicle and smart transportation (CVST) project that has inspired and embodied my research in the area of autonomous software systems.


Dr. Hamzeh Khazaei is a research associate at University of Toronto. Previously, he was a postdoctoral fellow in Adaptive System Research Lab at York University and a research scientist at IBM Canada Research and Development Centre, respectively. Dr. Khazaei received his PhD degree in Computer Science from University of Manitoba where he did research on performance engineering of distributed cloud systems. He obtained both his Masters and Bachelor degrees in computer science from Amirkabir University of Technology, Tehran, Iran. He has six years of industry experience in software engineering, cloud computing and big data management. His research on performance engineering, self-adaptive applications and big data has attracted high attention from government, media and research community through increased funding, frequent citations, a number of best paper awards and spotlight recognitions from top-tier journals and conferences. For more information, you may visit

Margaret Garabon
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