Comprehensive guide to the principles, algorithms, and techniques underlying resource management for clouds, big data, and sensor-based systems
Resource Management on Distributed Systems provides helpful guidance by describing algorithms and techniques for managing resources on parallel and distributed systems, including grids, clouds, and parallel processing-based platforms for big data analytics.
The book focuses on four general principles of resource management and their impact on system performance, energy usage, and cost, including end-of-chapter exercises. The text includes chapters on sensors, autoscaling on clouds, complex event processing for streaming data, and data filtering techniques for big data systems.
The book also covers results of applying the discussed techniques on simulated as well as real systems (including clouds and big data processing platforms), and techniques for handling errors associated with user predicted task execution times.
Written by a highly qualified academic with significant research experience in the field, Resource Management on Distributed Systems includes information on sample topics such as:
With comprehensive coverage of core topics in the field, Resource Management on Distributed Systems is a comprehensive guide to resource management in a single publication and is an essential read for professionals, researchers and students working with distributed systems.
"synopsis" may belong to another edition of this title.
Shikharesh Majumdar is Chancellor’s Professor & Director at Real Time and Distributed Systems Research Centre, Carleton University, Canada. Professor Majumdar earned his PhD in Computational Science from the University of Saskatchewan in 1988 and is a Senior Member of the IEEE and a Fellow of Institute of Engineering and Technology (IET). Professor Majumdar’s research interests include Parallel and Distributed Systems, Operating Systems, Middleware, and many more. He has had many papers published in Journals and Refereed Conference Proceedings, has provided various contributions to many books and is the recipient of multiple awards.
Comprehensive guide to the principles, algorithms, and techniques underlying resource management for clouds, big data, and sensor-based systems
Resource Management on Distributed Systems provides helpful guidance by describing algorithms and techniques for managing resources on parallel and distributed systems, including grids, clouds, and parallel processing-based platforms for big data analytics.
The book focuses on four general principles of resource management and their impact on system performance, energy usage, and cost, including end-of-chapter exercises. The text includes chapters on sensors, autoscaling on clouds, complex event processing for streaming data, and data filtering techniques for big data systems.
The book also covers results of applying the discussed techniques on simulated as well as real systems (including clouds and big data processing platforms), and techniques for handling errors associated with user predicted task execution times.
Written by a highly qualified academic with significant research experience in the field, Resource Management on Distributed Systems includes information on sample topics such as:
With comprehensive coverage of core topics in the field, Resource Management on Distributed Systems is a comprehensive guide to resource management in a single publication and is an essential read for professionals, researchers and students working with distributed systems.
"About this title" may belong to another edition of this title.
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