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Elastic traffic engineering subject to a fair bandwidth allocation via bilevel programming

Elastic traffic engineering subject to a fair bandwidth allocation via bilevel programming
Elastic traffic engineering subject to a fair bandwidth allocation via bilevel programming
The ability of TCP's congestion control scheme to adapt the rate of traffic flows and fairly use all the available resources is one of the Internet's pillars. So far, however, the elasticity of traffic has been disregarded in traffic engineering (TE) methodologies mainly because, only recently, the increase in access capacity has moved the bottlenecks from the access network to the operator network and hungry cloud-based applications have begun to use all the available bandwidth. We propose a new approach to TE with elastic demands which models the interaction between the network operator and the end-to-end congestion control scheme as a Stackelberg game. Given a set of elastic traffic demands only specified by their origin-destination pairs, the network operator chooses a set of routing paths (leader's problem) which, when coupled with the fair bandwidth allocation that the congestion control scheme would determine for the chosen routing (follower's problem), maximizes a network utility function. We present bilevel programming formulations for the above TE problem with two widely-adopted bandwidth allocation models, namely, max-min fairness and proportional fairness, and derive corresponding exact and approximate single-level mathematical programming reformulations. After discussing some key properties, we report on computational results obtained for different network topologies and instance sizes. Interestingly, even feasible solutions to our bilevel TE problems with large optimality gaps yield substantially higher network utility values than those obtained by solving a standard single-level TE problem and then fairly reallocating the bandwidth a posteriori.
Stackelberg games, Traffic engineering, bilevel programming, elastic traffic, max-min fairness, proportional fairness
1-14
Coniglio, Stefano
03838248-2ce4-4dbc-a6f4-e010d6fdac67
Gianoli, Luca Giovanni
272c06d0-8b63-48dd-96ae-781ec6a6479f
Amaldi, Edoardo
eefad18b-86c1-4a8f-a931-23e8ddd59d6e
Capone, Antonio
63fecc3a-2392-4f5b-ae14-36cb627bdabd
Coniglio, Stefano
03838248-2ce4-4dbc-a6f4-e010d6fdac67
Gianoli, Luca Giovanni
272c06d0-8b63-48dd-96ae-781ec6a6479f
Amaldi, Edoardo
eefad18b-86c1-4a8f-a931-23e8ddd59d6e
Capone, Antonio
63fecc3a-2392-4f5b-ae14-36cb627bdabd

Coniglio, Stefano, Gianoli, Luca Giovanni, Amaldi, Edoardo and Capone, Antonio (2020) Elastic traffic engineering subject to a fair bandwidth allocation via bilevel programming. IEEE/ACM Transactions on Networking, 28 (6), 1-14, [9170527]. (doi:10.1109/tnet.2020.3007572).

Record type: Article

Abstract

The ability of TCP's congestion control scheme to adapt the rate of traffic flows and fairly use all the available resources is one of the Internet's pillars. So far, however, the elasticity of traffic has been disregarded in traffic engineering (TE) methodologies mainly because, only recently, the increase in access capacity has moved the bottlenecks from the access network to the operator network and hungry cloud-based applications have begun to use all the available bandwidth. We propose a new approach to TE with elastic demands which models the interaction between the network operator and the end-to-end congestion control scheme as a Stackelberg game. Given a set of elastic traffic demands only specified by their origin-destination pairs, the network operator chooses a set of routing paths (leader's problem) which, when coupled with the fair bandwidth allocation that the congestion control scheme would determine for the chosen routing (follower's problem), maximizes a network utility function. We present bilevel programming formulations for the above TE problem with two widely-adopted bandwidth allocation models, namely, max-min fairness and proportional fairness, and derive corresponding exact and approximate single-level mathematical programming reformulations. After discussing some key properties, we report on computational results obtained for different network topologies and instance sizes. Interestingly, even feasible solutions to our bilevel TE problems with large optimality gaps yield substantially higher network utility values than those obtained by solving a standard single-level TE problem and then fairly reallocating the bandwidth a posteriori.

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Elastic traffic engineering subject to a fair bandwidth allocation via bilevel programming paper - Accepted Manuscript
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More information

Accepted/In Press date: 30 June 2020
e-pub ahead of print date: 18 August 2020
Published date: December 2020
Additional Information: Publisher Copyright: © 1993-2012 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
Keywords: Stackelberg games, Traffic engineering, bilevel programming, elastic traffic, max-min fairness, proportional fairness

Identifiers

Local EPrints ID: 445402
URI: http://eprints.soton.ac.uk/id/eprint/445402
PURE UUID: 08fc573b-22be-41d4-a076-ac6e79ed4398
ORCID for Stefano Coniglio: ORCID iD orcid.org/0000-0001-9568-4385

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Date deposited: 07 Dec 2020 17:33
Last modified: 29 Oct 2022 01:49

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Contributors

Author: Luca Giovanni Gianoli
Author: Edoardo Amaldi
Author: Antonio Capone

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