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dc.contributor.authorBeal, Jacob
dc.contributor.authorGilbert, Seth
dc.date.accessioned2005-12-22T01:15:30Z
dc.date.available2005-12-22T01:15:30Z
dc.date.issued2003-12-17
dc.identifier.otherMIT-CSAIL-TR-2003-034
dc.identifier.otherAIM-2003-027
dc.identifier.urihttp://hdl.handle.net/1721.1/30439
dc.description.abstractWe 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.format.extent22 p.
dc.format.extent23886105 bytes
dc.format.extent803571 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesMassachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
dc.subjectAI
dc.subjectad-hoc networks distributed algorithms atomic distributed shared memory
dc.titleRamboNodes for the Metropolitan Ad Hoc Network


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