Load Balancing: An Automated Learning Approach

Pankaj Mehra/ Benjamin W. Wah

ISBN 10: 9810221355 / ISBN 13: 9789810221355

Published by World Scientific Pub Co Inc, 1995

About this Item

150 pages. 9.00x6.50x0.75 inches. In Stock.

Seller Inventory # 9810221355

Bibliographic Details

• Title: Load Balancing: An Automated Learning Approach
• Publisher: World Scientific Pub Co Inc
• Publication Date: 1995
• Language: English
• ISBN 10: 9810221355
• ISBN 13: 9789810221355
• Binding: Hardcover
• Condition: Brand New

About this title

Synopsis

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.

Synopsis

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 policies. Together, the system constitutes an automated strategy-learning system for performance-driven improvement of existing load-balancing software.