Dimensioning bandwidth for elastic traffic in high-speed data networks

Berger, Arno; Kogan, Yaakov

doi:10.1109/90.879350

Cited by 80 publications

(58 citation statements)

References 21 publications

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“…Several works on insensitivity (see, e.g., [9,11,17]) have shown (for systems fairly similar to the one we are studying) that the average performance parameters are insensitive to the distribution of ON and OFF periods. In Section 7, we present a comparison of the system performance obtained by simulation for several traffic distributions (exponential and Pareto), and our analytical model.…”

Section: Discussion Of the Modeling Assumptionsmentioning

confidence: 99%

An efficient analytical model for the dimensioning of WiMAX networks supporting multi-profile best effort traffic

Doirieux¹,

Baynat²,

Maqbool

et al. 2010

Computer Communications

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This paper tackles the challenging task of developing a simple and accurate analytical model for performance evaluation of WiMAX networks. The need for accurate and fast-computing tools is of primary importance to face complex and exhaustive dimensioning issues for this promising access technology. In this paper, we present a generic Markovian model developed for three usual scheduling policies (slot sharing fairness, throughput fairness and opportunistic scheduling) that provides closed-form expressions for all the required performance parameters instantaneously. We also present and evaluate the performance of a fourth policy, called throttling policy, that limits the maximum user throughput and makes use of the Maximum Sustained Traffic Rate (MSTR) parameter foreseen by the standard. At last, we extend these studies to multi-profile traffic patterns. The proposed models are compared in depth with realistic simulations that show their accuracy and robustness regarding the different modeling assumptions. Finally, the speed of our analytical tools allows us to carry on dimensioning studies that require several thousands of evaluations, which would not be tractable with any simulation tool.

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Section: Discussion Of the Modeling Assumptionsmentioning

confidence: 99%

An efficient analytical model for the dimensioning of WiMAX networks supporting multi-profile best effort traffic

Doirieux¹,

Baynat²,

Maqbool

et al. 2010

Computer Communications

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“…Now assume active users share the backhaul link in a fair way. The stationary distribution of the number of active users X is then given by [3,9]:…”

Section: No Access Ratesmentioning

confidence: 99%

“…In fact, the flow-level models of data networks can be considered as the analogues for the Erlang model of telephone networks and its extensions to multi-rate circuit-switched networks [5]. They have proved essential for both dimensioning [3,6,29,25,24,16] and traffic engineering [15,23,21,28].…”

Section: Introductionmentioning

confidence: 99%

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The multi-source model for dimensioning data networks

Bonald

Comte

2016

Computer Networks

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Traffic modeling is key to the dimensioning of data networks. Usual models rely on the implicit assumption that each user generates data flows in series, one after the other, the ongoing flows sharing equitably the considered network link. We relax this assumption and consider the more realistic case where users may generate several data flows in parallel, these flows having to share the user's access line as well. We qualify this model as multi-source since each user now behaves as an independent traffic source. Usual performance metrics like mean throughput and congestion rate must now be defined at user level rather than at flow level. We derive explicit expressions for these performance metrics under the assumption that flows share bandwidth according to balanced fairness. These results are compared with those obtained by simulation when max-min fairness is imposed, either at flow level or at user level.

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“…We focus on a single link and assume that all of the connections share the bottleneck link. Bandwidth dimensioning for elastic traffic in a single link's case is studied in [8] to satisfy a performance objective based on the mean probability of the per-connection bandwidth in high-speed data networks. The issue of dimensioning Internet access lines for elastic traffic is discussed in [9] using a M/G/R − P S model characterizing TCP traffic at flow level.…”

Section: Introductionmentioning

confidence: 99%

Grid Network Dimensioning by Modeling the Deadline Constrained Bulk Data Transfers

Munir

Primet²,

Welzl

2009

2009 11th IEEE International Conference on High Performance Computing and Communications

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Abstract-Grid applications need to move large amounts of data between distributed resources within deterministic time frames. In most cases it is possible to specify the volume and the deadline in advance. We formally define and analyze a mechanism of network reservations of bulk data transfer requests having opportunistic utilization of residual network capacity and analyze it using an M/M/1/N − RP S queue. We compare the analytical results of our mechanism with the analytical results obtained from an M/M/N/N queue, for the case in which there is no opportunistic sharing of residual capacity. We validate the analytical results through simulations in C++. The analytical model is also validated against ns-2 simulations taking into account network level details (IP and TCP protocols), showing remarkably good coherence even under heavy loads. The model is orders of magnitude faster than simulation, which enables its application for capacity planning of Grid networks (also known as network dimensioning), and to enforce Connection Admission Control (CAC) under the practical hypothesis of a dominating bottleneck on the transfer route.

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Dimensioning bandwidth for elastic traffic in high-speed data networks

Cited by 80 publications

References 21 publications

An efficient analytical model for the dimensioning of WiMAX networks supporting multi-profile best effort traffic

An efficient analytical model for the dimensioning of WiMAX networks supporting multi-profile best effort traffic

The multi-source model for dimensioning data networks

Grid Network Dimensioning by Modeling the Deadline Constrained Bulk Data Transfers

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