TY - GEN
T1 - Rethinking Internet traffic management
T2 - 2007 ACM CoNEXT Conference - 3rd International Conference on Emerging Networking EXperiments and Technologies, CoNEXT
AU - He, Jiayue
AU - Suchara, Martin
AU - Bresler, Ma'ayan
AU - Rexford, Jennifer L.
AU - Chiang, Mung
N1 - Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - In the Internet today, traffic management spans congestion control (at end hosts), routing protocols (on routers), and traffic engineering (by network operators). Historically, this division of functionality evolved organically. In this paper, we perform a top-down redesign of traffic management using recent innovations in optimization theory. First, we propose an objective function that captures the goals of end users and network operators. Using all known optimization decomposition techniques, we generate four distributed algorithms that divide traffic over multiple paths based on feedback from the network links. Combining the best features of the algorithms, we construct TRUMP: a traffic management protocol that is distributed, adaptive, robust, flexible and easy to manage. Further, TRUMP can operate based on implicit feedback about packet loss and delay. We show that using optimization decompositions as a foundation, simulations as a building block, and human intuition as a guide can be a principled approach to protocol design.
AB - In the Internet today, traffic management spans congestion control (at end hosts), routing protocols (on routers), and traffic engineering (by network operators). Historically, this division of functionality evolved organically. In this paper, we perform a top-down redesign of traffic management using recent innovations in optimization theory. First, we propose an objective function that captures the goals of end users and network operators. Using all known optimization decomposition techniques, we generate four distributed algorithms that divide traffic over multiple paths based on feedback from the network links. Combining the best features of the algorithms, we construct TRUMP: a traffic management protocol that is distributed, adaptive, robust, flexible and easy to manage. Further, TRUMP can operate based on implicit feedback about packet loss and delay. We show that using optimization decompositions as a foundation, simulations as a building block, and human intuition as a guide can be a principled approach to protocol design.
UR - http://www.scopus.com/inward/record.url?scp=56749132464&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=56749132464&partnerID=8YFLogxK
U2 - 10.1145/1364654.1364676
DO - 10.1145/1364654.1364676
M3 - Conference contribution
AN - SCOPUS:56749132464
SN - 9781595937704
T3 - Proceedings of 2007 ACM CoNEXT Conference - 3rd International Conference on Emerging Networking EXperiments and Technologies, CoNEXT
BT - Proceedings of 2007 ACM CoNEXT Conference - 3rd International Conference on Emerging Networking EXperiments and Technologies, CoNEXT
Y2 - 10 December 2007 through 13 December 2007
ER -