Load balancing [electronic resource] : an automated learning approach / Pankaj Mehra, Benjamin W. Wah.
By: Mehra, Pankaj
.
Contributor(s): Wah, Benjamin W.
Material type: 
Computer filePublisher: Singapore : World Scientific Publishing Co. Pte Ltd., ©1995Description: 1 online resource (156 p.) : ill.ISBN: 9789812831224.Subject(s): Electronic data processing -- Distributed processing | Computer capacity -- Planning | Electronic booksDDC classification: 005.4/3 Online resources: Access to full text is restricted to subscribers. Summary: "This book presents a system that learns new load indices and tunes the parameters of given migration policies. The key component is a dynamic workload generator that allows off-line measurement of task-completion times under a wide variety of precisely controlled loading conditions. The workload data collected are used for training comparator neural networks, a novel architecture for learning to compare functions of time series and for generating a load index to be used by the load balancing strategy. Finally, the load-index traces generated by the comparator networks are used in a population-based learning system for tuning the parameters of a given load-balancing policy. Together, the system constitutes an automated strategy-learning system for performance-driven improvement of existing load-balancing software."-- Publisher's website.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Title from web page (viewed December 7, 2018).
Includes bibliographical references and index.
"This book presents a system that learns new load indices and tunes the parameters of given migration policies. The key component is a dynamic workload generator that allows off-line measurement of task-completion times under a wide variety of precisely controlled loading conditions. The workload data collected are used for training comparator neural networks, a novel architecture for learning to compare functions of time series and for generating a load index to be used by the load balancing strategy. Finally, the load-index traces generated by the comparator networks are used in a population-based learning system for tuning the parameters of a given load-balancing policy. Together, the system constitutes an automated strategy-learning system for performance-driven improvement of existing load-balancing software."-- Publisher's website.
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