Computation and Data Intensive Parallel and Distributed Systems: Resource Management and Data Handling Techniques

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The availability of computing and communication systems at a reasonable cost is increasing the use of parallel and distributed systems. Distributed systems in general and internet-based systems such as the cloud in particular are becoming part of the daily life in a modern society. There are two new important challenges facing the researchers of parallel and distributed systems. They concern the effective handling of (i) large volumes of data often referred to as Big Data and (ii) the high proliferation of sensor-based devices that utilize the newly emerging internet of things (IoT) technology. The proposed research is motivated by the need for finding effective answers to these challenges.*** The large resource pools in clouds are often utilized in systems that concern Big Data and IoT. Resource management and data handing techniques are critically needed, however, for harnessing this underlying resource pool of a cloud. My proposed research is directed at filling the gap in the current state of the art concerning techniques for resource management and data handling for this relatively new domain of high performance and data intensive systems. Research is proposed for resource management and data handling techniques for (i) cloud based data analytics platforms that are crucial for extracting knowledge from BigData and (ii) smart systems (e.g. sensor-based bridges, buildings, aerospace machinery and smart health care systems) that are essential components of the newly emerging smart society. The research results will cerate 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 the past 29 years. My work includes pioneering research on parallel job scheduling on multiprogrammed parallel systems and novel techniques for managing a large heterogeneous set of resources and handling error-prone user estimates of request run times on clouds. My contributions are recognized through best paper/presentation awards and selection as a Distinguished Visitor for the IEEE Computer Society. My activities in the past 6 years are reflected in 15 journal and 1 magazine contributions, 4 book chapters, 36 refereed conference papers, 3 posters, 5 keynote addresses and 12 invited lectures, service in various program and steering committees for reputed conferences, 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 (see CCV).