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#Packetstream inc full

The design of the idEEC scheme was motivated by AT&T's need to monitor the BER-which reflect the channel conditions-of their wireless access links, over which insertion, deletion, and bit flipping errors could happen.

Second, they have designed a new type of error-estimating codes (EEC), called idEEC (insertion/deletion EEC), for measuring the BER (bit error rate) of wireless transmissions. They have also proved that, surprisingly, it is impossible to intersect three or more sketches (in an attempt to extract even more information), when these sketches belong to the most popular and frequently used Gaussian sketch family. Through this work, they have realized the vision laid out in the proposal on extracting information via intersecting two sketch (synopsis) data structures. First, they worked with researchers at AT&T Labs to develop a new technique, called Crossroads, for summarizing large data sets that can be used to mine logs of cellular voice and data traffic for rapid diagnosis of network performance anomalies, an important research objective of this NSF project. students of PI Xu's have worked together with collaborators on three research problems closely related to this project. Intellectual merit: Co-PIs Lall and Xu, and Ph.D. Their policies may differ from this site. Some links on this page may take you to non-federal websites.

#Packetstream inc full

Some full text articles may not yet be available without a charge during the embargo (administrative interval). When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH As part of the transfer of research findings into commercial practice the PIs will collaborate with members of AT&T's Network Management and Engineering Department. In terms of commercial impact, the project will lead to better methods for the diagnosis of large-scale networks, thereby reducing the cost to maintain and operate them. In addition to publishing in appropriate scientific venues, the PIs will expand the Wikipedia entries on topics related to data streaming algorithms as part of the process of disseminating general information about the topic area to the scientific community. Additionally, the project will integrate education and research via inclusion of the research into courses. Undergraduates at Georgia Tech, Denison and other institutions will be recruited via undergraduate workshops and research symposiums.

Broader Impact: The project will provide research experience for undergraduates.

#Packetstream inc how to

Specific areas to be studied for purposes of developing sampling techniques include identifying what constitutes the representative flows for troubleshooting purposes and investigating how to best encode and decode the sampled data, and how the samples can be gracefully shrunk over time so as to reclaim space for new data as they arrive. The project will develop the algorithms and mathematical theory needed to design intelligent sampling algorithms for compressing network traffic. The project's objective is to extract from high-speed packet streams on individual network links an approximate and highly compressed representation of the link traffic that is orders of magnitude smaller in size than the raw traffic stream but which permits almost the same degree of troubleshooting as the raw data. This project will explore mathematical techniques and network tools that will reduce the amount of data that has to be captured and stored while still allowing network operators to troubleshoot their networks. The high-speed link techniques that work on LANs, such as dumping packets and analyzing the detailed traffic, are impossible due to massive data volume. Troubleshooting undesirable network events, such as poor connectivity or performance, is difficult at best. Primary Place of Performance Congressional District:

Ashwin Lall (Principal Investigator) Sponsored Research Office:.

John Brassil CNS Division Of Computer and Network Systems CSE Direct For Computer & Info Scie & Enginr NeTS: Small: Collaborative Research: Towards Principled Network Troubleshooting via Efficient Packet Stream Processing NSF Org:ĬNS Division Of Computer and Network Systems