mbm@helmut.scs.carleton.ca (Max B. Maklin) (12/19/90)
I am posting in hope of finding relevant sources to the problem of learning intelligent load balancing in a distributed system. The system may be either homogeneous or hetergeneous, but I am inclined to hetergeneous systems. I am interested in any readings, (i.e., tech reports, journals, articles, thesis, dissertions, etc.) on the application of sub-symbolic learning to adaptive, dynamic load-balancing in distributed systems, especially those which are loosely-coupled systems (i.e., communication costs are of importance). The types of learning techniques I would like to employ include neural networks, learning automata, and genetic algorithms, solely, or in conjuction, but would be interested to hear from others who have used different techniques. I would also be interested in hearing from any other fellow researchers interested in similar notions for possible correspondance and exchange of results. I would appreciate that all replys be sent to my address and if there is enough response, I would be happy to post it to the relevent news groups at a later time. -- +-----------------------------------------------------------------+ | Max Maklin | | | School of Computer Science | e-mail: mbm@hans.scs.carleton.ca | | Carleton University | | | Ottawa, CAN K1S 5B6 | | +-----------------------------------------------------------------+