Load Balancing: An Automated Learning Approach

Pankaj Mehra · Benjamin W Wah

апр. 1995 г. · World Scientific Publishing Company

Об электронной книге

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.

Об авторе

Pankaj Mehra (Indian Institute of Technology, India);Benjamin W Wah (University of Illinois at Urbana-Champaign)