Insensitive bandwidth sharing

Bonald, Thomas; Proutière, Alexandre

doi:10.1109/glocom.2002.1189112

Cited by 60 publications

(147 citation statements)

References 14 publications

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“…The steady state distribution depends on the traffic characteristics only via traffic load in each class. Using this resource sharing scheme, the performance remains unchanged under very relaxed conditions on the arrival process and flow size distribution [2]. It may also be used as an approximation of utility based sharing schemes such as proportional fairness.…”

Section: B Bf Analysismentioning

confidence: 95%

“…Balanced fairness is a resource sharing notion that forces the system to be reversible [2]. Reversibility allows deriving the (non-normalized) steady state distribution recursively stateby-state without the need for matrix inversion and we may consider a significantly larger number of states in the state space truncation resulting in higher accuracy.…”

Section: B Bf Analysismentioning

confidence: 99%

“…Balanced fairness is a resource sharing scheme developed by Bonald and Proutière [2], which makes the dynamic system more tractable. An appealing feature of the BF approach is that its performance is insensitive to traffic details.…”

Section: Introductionmentioning

confidence: 99%

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Flow Level Performance Analysis of Wireless Data Networks: A Case Study

Leino¹,

Penttinen²,

Virtamo³

2006

2006 IEEE International Conference on Communications

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Abstract-We give an example of flow level performance analysis of data traffic in wireless networks by studying a scenario where two base stations with link adaptation serve in a coordinated fashion downloading users on a road or street between the stations. Due to the dynamic nature of such systems, a detailed flow level analysis is challenging and conventional methods run into computational difficulties. We motivate the detailed analysis by studying the system under different operational goals such as maximum throughput, max-min fairness and balanced fairness, concluding that the performance under these dynamic policies differ significantly from the performance under more tractable static policies. We discuss how the corresponding numerical analyses can be facilitated by applying the notion of balanced fairness and, in particular, introduce a novel approximation method referred to as value extrapolation. Value extrapolation can be applied to approximate any performance measure expressed as the expected value of a random variable which is a function of the system state. The idea of the value extrapolation is to consider the system in the MDP (Markov Decision Processes) setting and to solve the expected value from the Howard equations written for a truncated state space. Instead of a simple truncation, the relative values of states just outside the truncated state space are estimated using a polynomial extrapolation based on the states inside. This leads to a closed system and, unless the system is heavily loaded, allows one to obtain accurate results with remarkably small truncated state spaces.

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Section: B Bf Analysismentioning

confidence: 95%

Section: B Bf Analysismentioning

confidence: 99%

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Flow Level Performance Analysis of Wireless Data Networks: A Case Study

Leino¹,

Penttinen²,

Virtamo³

2006

2006 IEEE International Conference on Communications

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“…, n − 1}. We assume that the active sessions are served according to a processor sharing discipline with state-dependent service rate [20,21]. Insensitivity of the stationary probability distribution π k with respect to the file size and think time distributions follows from an approach similar to that in [6], or can alternatively be derived from the results in [21].…”

Section: Concurrent Tcp Sessions: a Queueing Modelmentioning

confidence: 99%

A queueing model for HTTP traffic over IEEE 802.11 WLANs

2006

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We consider an IEEE 802.11 based wireless LAN where an access point is used to connect a fixed number of users to the Web or to a shared file system. Users alternate between activity periods (corresponding to the download of a file) and idle periods (corresponding to think times). We first consider the interaction of TCP with the IEEE 802.11 MAC protocol, and get approximate expressions for the TCP throughput in the presence of n c competing persistent connections. This result is then used to develop a queueing model, which provides the mean session delay in the presence of short-lived flows. The analysis also accounts for the TCP delayed ACK option. Comparison with simulation outcomes is provided, validating the model and providing guidelines for network designers. A particular emphasis is devoted to the impact of the TCP's advertised window size; in particular, it is proved that setting it to a small value leads to insensitivity of mean file transfer times to the file size distribution.

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“…Mo and Walrand [28] propose this as a decoupled fairness criteria, which each user can use to achieve fairness without considering the behavior of other users. Bonald and Proutiere [4] introduce the notion of balanced fairness, referring to allocations for which the steady state distribution is insensitive to any traffic characteristics except the traffic intensities. They note that this insensitivity property does not hold for utility-based allocations such as max-min and proportional fairness, where an optimal allocation process depends on detailed traffic characteristics such as flow arrival process and flow size distribution.…”

Section: Notion Of Fairness In Networkingmentioning

confidence: 99%

A new QoE fairness index for QoE management

et al. 2018

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The user-centric management of networks and services focuses on the Quality of Experience (QoE) as perceived by the end user. In general, the goal is to maximize (or at least ensure an acceptable) QoE, while ensuring fairness among users, e.g., in terms of resource allocation and scheduling in shared systems. A problem arising in this context is that the notions of fairness commonly applied in the QoS domain do not translate well to the QoE domain. We have recently proposed a QoE fairness index F, which solves these issues. In this paper, we provide a detailed rationale for it, along with a thorough comparison of the proposed index and its properties against the most widely used QoS fairness indices, showing its advantages. We furthermore explore the potential uses of the index, in the context of QoE management and describe future research lines on this topic.

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Insensitive bandwidth sharing

Cited by 60 publications

References 14 publications

Flow Level Performance Analysis of Wireless Data Networks: A Case Study

Flow Level Performance Analysis of Wireless Data Networks: A Case Study

A queueing model for HTTP traffic over IEEE 802.11 WLANs

A new QoE fairness index for QoE management

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