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Rethinking traffic management: Desig...

He, Jiayue.

Rethinking traffic management: Design of optimizable networks.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Rethinking traffic management: Design of optimizable networks.
Author:	He, Jiayue.
Description:	136 p.
Notes:	Advisers: Mung Chiang; Jennifer Rexford.
Notes:	Source: Dissertation Abstracts International, Volume: 69-03, Section: B, page: 1827.
Contained By:	Dissertation Abstracts International69-03B.
Subject:	Engineering, Electronics and Electrical.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3308043
ISBN:	9780549553823

Rethinking traffic management: Design of optimizable networks.
He, Jiayue.

Rethinking traffic management: Design of optimizable networks. - 136 p.

Advisers: Mung Chiang; Jennifer Rexford.

Thesis (Ph.D.)--Princeton University, 2008.

In the 'top-down' approach, we propose a new objective function that captures the goals of both end users and network operators. Next, using various optimization decomposition techniques, we generate four distributed algorithms that divide traffic over multiple paths based on feedback from the network links. These distributed algorithms are provably stable and optimal, but can converge slowly and are sensitive to tuning parameters. Finally, combining the best features of these distributed algorithms, we construct TRUMP: TRaffic-management Using Multipath Protocol. TRUMP converges quickly and contains a single easy to tune parameter. Packet-level simulations show TRUMP behaves well with realistic topologies, feedback delays, capacities, and traffic loads.

ISBN: 9780549553823Subjects--Topical Terms:

226981
Engineering, Electronics and Electrical.

Rethinking traffic management: Design of optimizable networks.
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020 $a 9780549553823
035 $a 00372057
040 $a UMI $c UMI
100 $a He, Jiayue. $3 321779
245 1 0 $a Rethinking traffic management: Design of optimizable networks.
300 $a 136 p.
500 $a Advisers: Mung Chiang; Jennifer Rexford.
500 $a Source: Dissertation Abstracts International, Volume: 69-03, Section: B, page: 1827.
502 $a Thesis (Ph.D.)--Princeton University, 2008.
520 $a In the 'top-down' approach, we propose a new objective function that captures the goals of both end users and network operators. Next, using various optimization decomposition techniques, we generate four distributed algorithms that divide traffic over multiple paths based on feedback from the network links. These distributed algorithms are provably stable and optimal, but can converge slowly and are sensitive to tuning parameters. Finally, combining the best features of these distributed algorithms, we construct TRUMP: TRaffic-management Using Multipath Protocol. TRUMP converges quickly and contains a single easy to tune parameter. Packet-level simulations show TRUMP behaves well with realistic topologies, feedback delays, capacities, and traffic loads.
520 $a Overall, we show that using optimization theory as a foundation, simulations as a building block, and engineering intuition as a guide can be a principled approach to architecture and protocol design.
520 $a Since applications today may have different performance objectives, we next redesign traffic management to handle multiple traffic classes. A natural objective for an ISP is to maximize aggregate performance objectives across multiple traffic classes. Decomposing the ISP's problem leads to a stable and optimal solution where each traffic class optimizes according to its own performance objective, with an algorithm to dynamically allocate bandwidth shares. The distributed protocols can be implemented using DaVinci: Dynamically Adaptive VIrtual Networks for a Customized Internet. In DaVinci, each virtual network runs traffic-management protocols optimized for a traffic class, and link bandwidth is dynamically allocated between virtual networks through separate queues.
520 $a Traffic management refers to controlling how much traffic traverses each path in a network. On the Internet today, end hosts run congestion control to adapt sending rates, routers route traffic on shortest paths based on link weights, and operators tune link weights to direct traffic away from heavily-loaded links. This dissertation performs a top-down redesign of traffic management to support diverse application requirements, leveraging emerging technology trends in network virtualization and multipath routing.
520 $a We begin by analyzing, then redesigning today's traffic-management system. In the 'bottom-up' approach, we study the interaction of congestion control and traffic engineering using established optimization models. We find congestion control and traffic-engineering interact in a stable, though not always efficient manner. Efficiency can be improved by tuning the operator's traffic-engineering function, but at the cost of robustness.
590 $a School code: 0181.
650 $a Engineering, Electronics and Electrical. $3 226981
650 $a Computer Science. $3 212513
690 $a 0544
690 $a 0984
710 $a Princeton University. $3 212488
773 0 $g 69-03B. $t Dissertation Abstracts International
790 $a 0181
790 1 0 $a Chiang, Mung, $e advisor
790 1 0 $a Rexford, Jennifer, $e advisor
791 $a Ph.D.
792 $a 2008
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