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Craig Partridge
Researcher at BBN Technologies
Publications - 111
Citations - 11797
Craig Partridge is an academic researcher from BBN Technologies. The author has contributed to research in topics: Network packet & The Internet. The author has an hindex of 39, co-authored 109 publications receiving 11492 citations. Previous affiliations of Craig Partridge include Harvard University & National Research Council.
Papers
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Recommendations on Queue Management and Congestion Avoidance in the Internet
B. Braden,David D. Clark,Jon Crowcroft,Bruce S. Davie,S. Deering,Deborah Estrin,Sally Floyd,Van Jacobson,Greg Minshall,Craig Partridge,Larry L. Peterson,Kadangode K. Ramakrishnan,Scott Shenker,John Wroclawski,Lixia Zhang +14 more
TL;DR: This memo presents a strong recommendation for testing, standardization, and widespread deployment of active queue management in routers, to improve the performance of today's Internet.
Specification of Guaranteed Quality of Service
TL;DR: This memo describes the network element behavior required to deliver a guaranteed service (guaranteed delay and bandwidth) in the Internet and follows the service specification template described in [1].
Distance Vector Multicast Routing Protocol
TL;DR: This RFC describes a distance-vector-style routing protocol for routing multicast datagrams through an internet, derived from the Routing Information Protocol, and implements multicasting as described in RFC-1054.
Proceedings ArticleDOI
Hash-based IP traceback
Alex C. Snoeren,Craig Partridge,Luis Sanchez,Christine Elaine Jones,Fabrice Tchakountio,Stephen T. Kent,W. Timothy Strayer +6 more
TL;DR: This work presents a hash-based technique for IP traceback that generates audit trails for traffic within the network, and can trace the origin of a single IP packet delivered by the network in the recent past and is implementable in current or next-generation routing hardware.
Proceedings ArticleDOI
A knowledge plane for the internet
TL;DR: It is argued that cognitive techniques, rather than traditional algorithmic approaches, are best suited to meeting the uncertainties and complexity of the objective of network research.