High Performance Parallel and Distributed Systems: Resource Management and Data Handling Techniques

点击翻译按钮获取中文摘要

The proposed research focuses on resource management and data handling techniques on high performance parallel and distributed systems including clusters and clouds. Computation and data intensive BigData analytics applications used in the context of enterprise and social media as well on sensor-based smart systems (e.g. smart bridges, buildings, machinery and health care systems) often require the power of such high performance environments. There are two important challenges currently facing the researchers of such systems: processing and analysis of (i) large volumes of stored data and (ii) streaming data resulting from twitter feeds and continuously generated sensor data for example. Each of these is important in the context of today's data and computation intensive systems. Effective resource management and data handling techniques are crucial for achieving high performance and high quality of experience for the users on such systems. New cost effective techniques are critically needed for harnessing the underlying large resource pools in clouds that are often used to meet the challenges of such data and computation intensive applications and produce results in a timely manner. Proposed research is directed at achieving these required innovations in science and technology. Outcomes & Benefits: Results of the research will be applicable to both researchers and users in two important domains: (a) cloud based data analytics platforms that are crucial for extracting knowledge from BigData and (b) smart systems that are essential components of the newly emerging smart society. The research results will create new knowledge, advance the state of the art and contribute to the achievement of the desired quality of service for system users, adequate revenues for service providers, safe and economically maintained infrastructures and machinery as well as efficient health care systems for the public. Training of students is an important and an integral part of the plan; the research results and trained HQP will aid in establishing Canada as a leader in the global market. I have been researching distributed systems and resource management for many years with recent focus on clouds and data analytics platforms. My contributions are recognized through best paper awards and selection as a Distinguished Visitor for the IEEE Computer Society. My activities in the past 6 years are reflected in my selection as a Fellow of the Institution of Engineering and Technology, 58 refereed contributions in reputed international forums, 4 keynote addresses, 1 plenary address and 13 invited lectures (including 2 tutorials), chairing of an international conference and the organization of several international workshops. Relevance of my research for the public is captured in my media interviews and the featuring of my research in the Scientia magazine.