Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6734
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dc.creatorBeal, Jacob-
dc.creatorGilbert, Seth-
dc.date2004-10-08T20:43:07Z-
dc.date2004-10-08T20:43:07Z-
dc.date2003-12-17-
dc.date.accessioned2013-10-09T02:46:42Z-
dc.date.available2013-10-09T02:46:42Z-
dc.date.issued2013-10-09-
dc.identifierAIM-2003-027-
dc.identifierhttp://hdl.handle.net/1721.1/6734-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/1721-
dc.descriptionWe present an algorithm to store data robustly in a large, geographically distributed network by means of localized regions of data storage that move in response to changing conditions. For example, data might migrate away from failures or toward regions of high demand. The PersistentNode algorithm provides this service robustly, but with limited safety guarantees. We use the RAMBO framework to transform PersistentNode into RamboNode, an algorithm that guarantees atomic consistency in exchange for increased cost and decreased liveness. In addition, a half-life analysis of RamboNode shows that it is robust against continuous low-rate failures. Finally, we provide experimental simulations for the algorithm on 2000 nodes, demonstrating how it services requests and examining how it responds to failures.-
dc.format22 p.-
dc.format1312502 bytes-
dc.format499111 bytes-
dc.formatapplication/postscript-
dc.formatapplication/pdf-
dc.languageen_US-
dc.relationAIM-2003-027-
dc.subjectAI-
dc.subjectad-hoc networks distributed algorithms atomic distributed shared memory-
dc.titleRamboNodes for the Metropolitan Ad Hoc Network-
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