Utility Proportional Fair Bandwidth Allocation: An Optimization Oriented Approach

Harks, Tobias

doi:10.1007/978-3-540-30573-6_5

Cited by 47 publications

(27 citation statements)

References 9 publications

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“…term U Non-GBR (R;X) in Eq. 7) when there is no distinction between using satellite or terrestrial capacity [23], which in our case is strictly valid for factor p Non-GBR =1. This is carried out by first distributing the satellite capacity among the BSs in proportion to the number of GBR connections handled per BS so that overall capacity left for GBR services is balanced across BSs.…”

Section: Traffic Distribution Strategy Algorithmmentioning

confidence: 71%

A traffic distribution scheme for 5G resilient backhauling using integrated satellite networks

Mendoza

Ferrús

Sallent

2017

2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)

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-Resilience and high availability are being considered as essential requirements in 5G networks. To fullfil these requirements, the integration of a satellite component within mobile backhaul networks is regarded as a compelling proposition to provide backup connectivity to critical cell sites and divert traffic from congested areas so that a limited capacity in their terrestrial links could be supplemented during peak-time or even replaced in case of total/partial failure or maintenance. Sustained in an architectural framework that enables the integration and management of the satellite capacity as a constituent part of a SDN-based traffic engineered mobile backhaul network, this paper develops and assesses a traffic distribution strategy that exploits the dynamically steerable satellite capacity provisioned for resilience purposes to maximize a network utility function under both failure and non-failure conditions in the terrestrial links.

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Section: Traffic Distribution Strategy Algorithmmentioning

confidence: 71%

A traffic distribution scheme for 5G resilient backhauling using integrated satellite networks

Mendoza

Ferrús

Sallent

2017

2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC)

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“…On the other hand, equal allocation of utilities, which is shown by the horizontal dashed line, labled by "equal utility", utilizes the network resource more efficiently. Therefore, utility fairness instead of rate fairness has been proposed for multiservice networks [3], [9].…”

Section: Weighting Factor Computation Schemementioning

confidence: 99%

Maintaining Utility Fairness Using Weighting Factors in Wireless Networks

Mehrjoo

Awad

Dianati

et al. 2009

GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

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Maintaining fairness using weighting factors is a common approach in resource allocation. However, computing weighting factors for multiservice wireless networks is not trivial because users' rate requirements are heterogeneous and their channel gains are variable. In this paper, we propose weighting factor computation and scheduling schemes for orthogonal frequency division multiple access (OFDMA) networks. The weighting factor computation scheme determines each user's share of rate for maintaining a utility notion of fairness. We then present a scheduling scheme which takes the users' weighting factors into consideration to allocate sub-carriers and power in OFDMA networks. The simulation results demonstrate that the proposed scheduling scheme outperforms an opportunistic scheme in terms of fairness performance in different scenarios, where the users are fixed or mobile.

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“…They also presented an algorithm for computing the allocation in polynomial number of iterations. In the meantime, Harks and Poschwatta [13], [14] introduced the concept of utility proportional fairness, where utilities' values of flows are enforced to achieve proportional fairness. They presented distributed algorithms to achieve the fairness although they did not consider the stability in the presence of round-trip delays.…”

Section: A Related Workmentioning

confidence: 99%

Utility max-min flow control using slope-restricted utility functions

Cho

Chong

2005

GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.

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Abstract-We present a network architecture for the distributed utility max-min flow control of elastic and nonelastic flows where utility values of users (rather than data rates of users) are enforced to achieve max-min fairness. The proposed link algorithm converges to utility max-min fair bandwidth allocation in the presence of round-trip delays without using the information of users' utility functions. To show that the proposed algorithm can be stabilized not locally but globally, we found that the use of nonlinear control theory is inevitable. Even though we use a distributed flow-control algorithm, it is shown that any kind of utility function can be used as long as the minimum slopes of the functions are greater than a certain positive value. Though our analysis is limited to the single-bottleneck and homogeneous-delay case, we believe that the proposed algorithm is the first to achieve utility max-min fairness with guaranteed stability in a distributed manner.

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Utility Proportional Fair Bandwidth Allocation: An Optimization Oriented Approach

Cited by 47 publications

References 9 publications

A traffic distribution scheme for 5G resilient backhauling using integrated satellite networks

A traffic distribution scheme for 5G resilient backhauling using integrated satellite networks

Maintaining Utility Fairness Using Weighting Factors in Wireless Networks

Utility max-min flow control using slope-restricted utility functions

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