Future Generation Computer Systems - Special issue on metacomputing
Data management and transfer in high-performance computational grid environments
Parallel Computing - Parallel data-intensive algorithms and applications
AGARM: an adaptive grid application and resource monitor framework
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
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The problem with practical, large-scale deployment of Grid monitoring system is that, it takes considerable management cost and skills to maintain the level of quality required by production usage, since the monitoring system will be fundamentally be distributed, need to be running continuously, and will itself likely be affected by the various faults and dynamic reconfigurations of the Grid itself. Although their automated management would be desirable,there are several difficulties, distributed faults and reconfigurations, component interdependencies, and scaling to maintain performance while minimizing probing effect. Given our goal to develop a generalized autonomous management framework for Grid monitoring, we have built a prototype, on top of NWS, featuring automatic configuration of its "clique" groups as well as coping with single-node faults without user intervention. An experimental deployment on the Tokyo Institute of Technology's Campus Grid (The Titech Grid) consisting of over 15 sites and 800 processors has shown the system to be robust in handling faults and reconfigurations, automatically deriving an ideal clique configuration for the head login nodes of each PC cluster in less than two minutes.