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#11
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Ok, I've checked it all again, so I'm a little more aware of the situation now. Until now I had little insight in the working of the algorithm. So I'm slightly less confused now.. ;-) The timing constraints are indeed important, as suggested. The algorithm is a heuristic selfcalibrating algorithm for a processing environment and tries to search the most ideal situation (eliminating noise etc). What should be done is: Send data to all nodes in the cluster, and the nodes get a specific amount of time to compute this data. The only difference between the nodes is the parameterset they get. Then some node will decide (compute) which node has the best result. This will be the calibrating parameters. This is why I propose the three structure, it avoids great message distribution in an all to all structure (stronger knowledge of who is all isn't always available) In general the systems do their work almost solitair. And dataset/message exchange should be minimized, because it gives overhead. So again do you think think the tree structure would suffice, or would another structure do a better job? A Centralized database would probably congest (alltough it's a pretty fast) network connection between the machines, and a lot of versioning has to be done, to compare all different results. Bram |
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