An achievability result for random networks
Abstract
We analyze a network of nodes in which pairs communicate over a shared wireless medium. We are interested in the maximum total aggregate traffic flow that is possible through the network. Our model differs substantially from the many existing approaches in that the channel connections in our network are entirely random: we assume that, rather than being governed by geometry and a decay law, the strength of the connections between nodes is drawn independently from a common distribution. Such a model is appropriate for environments where the first order effect that governs the signal strength at a receiving node is a random event (such as the existence of an obstacle), rather than the distance from the transmitter. We show that the aggregate traffic flow is a strong function of the channel distribution. In particular, we show that for certain distributions, the aggregate traffic flow scales at least as n/((log n)^v) for some fixed v > 0, which is significantly larger than the O(√n) results obtained for many geometric models.
Additional Information
© 2005 IEEE. This work is supported in part by the National Science Foundation under grant nos. CCR-0133818 and CCR-0326554, by the David and Lucille Packard Foundation, and by Caltech's Lee Center for Advanced Networking.Attached Files
Published - 01523477.pdf
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Additional details
- Eprint ID
- 54619
- Resolver ID
- CaltechAUTHORS:20150210-070353237
- NSF
- CCR-0133818
- NSF
- CCR-0326554
- David and Lucille Packard Foundation
- Caltech Lee Center for Advanced Networking
- Created
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2015-02-10Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field