Please use this identifier to cite or link to this item:
|Web of Science®
|Using end-to-end data to infer lossy links in sensor networks
|IEEE INFOCOM 2006 Proceedings of the 25th IEEE International Conference on Computer Communications, 2006: pp.1-12
|Annual Joint conference of the IEEE Computer and Communications Societies (25th : 2006 : Barcelona, Spain)
|Teletraffic Research Centre for Mathematical Modelling
|Hung X. Nguyen and Patrick Thiran
|Compared to wired networks, sensor networks pose two additional challenges for monitoring functions: they support much less probing traffic, and they change their routing topologies much more frequently. We propose therefore to use only endto- end application traffic to infer performance of internal network links. End-to-end data do not provide sufficient information to calculate link loss rates exactly, but enough to identify poorly performing (lossy) links.We introduce inference techniques based on Maximum likelihood and Bayesian principles, which handle well noisy measurements and routing changes. We evaluate the performance of both inference algorithms in simulation and on real network traces. We find that these techniques achieve high detection and low false positive rates.
|Appears in Collections:
|Aurora harvest 5
Mathematical Sciences publications
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.