Published June 12, 2000
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Power Laws, Highly Optimized Tolerance, and Generalized Source Coding
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Abstract
We introduce a family of robust design problems for complex systems in uncertain environments which are based on tradeoffs between resource allocations and losses. Optimized solutions yield the "robust, yet fragile" features of highly optimized tolerance and exhibit power law tails in the distributions of events for all but the special case of Shannon coding for data compression. In addition to data compression, we construct specific solutions for world wide web traffic and forest fires, and obtain excellent agreement with measured data.
Additional Information
©2000 The American Physical Society Received 3 November 1999; revised 17 March 2000 We thank Joshua Socolar for his insightful comments and suggestions. This work was supported by the David and Lucile Packard Foundation, NSF Grant No. DMR-9813752, a DOD MURI Grant for "Uncertainty management in complex systems," Caltech's Lee Center for Advanced Networking, and EPRI/DOD through the program in Complex Interactive Networks.Files
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- 1524
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- CaltechAUTHORS:DOYprl00
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2006-01-26Created from EPrint's datestamp field
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2021-11-08Created from EPrint's last_modified field