Centralized network utility maximization over aggregate flows

Gupta, Riten; Vandenberghe, Lieven; Gerla, Mário

doi:10.1109/wiopt.2016.7492926

Cited by 9 publications

(4 citation statements)

References 20 publications

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“…To this end, WNOS first determines a decomposition approach based on the mathematical structure of the network control problem, including whether the problem involves one or multiple sessions, what protocol layers are to be optimized, if the problem is convex or not, among others. Different decomposition approaches can lead to different structures of the resulting distributed control program with various convergence properties, communication overhead, and achievable network performance [8], [9], [10], [11].…”

Section: Wnos Architecturementioning

confidence: 99%

WNOS: Enabling Principled Software-Defined Wireless Networking

Guan

Bertizzolo

Demirors

et al. 2021

IEEE/ACM Trans. Networking

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This article investigates the basic design principles for a new Wireless Network Operating System (WNOS), a radically different approach to software-defined networking (SDN) for infrastructure-less wireless networks. Departing from wellunderstood approaches inspired by OpenFlow, WNOS provides the network designer with an abstraction hiding (i) the lowerlevel details of the wireless protocol stack and (ii) the distributed nature of the network operations. Based on this abstract representation, the WNOS takes network control programs written on a centralized, high-level view of the network and automatically generates distributed cross-layer control programs based on distributed optimization theory that are executed by each individual node on an abstract representation of the radio hardware.We first discuss the main architectural principles of WNOS. Then, we discuss a new approach to automatically generate solution algorithms for each of the resulting subproblems in an automated fashion. Finally, we illustrate a prototype implementation of WNOS on software-defined radio devices and test its effectiveness by considering specific cross-layer control problems. Experimental results indicate that, based on the automatically generated distributed control programs, WNOS achieves 18%, 56% and 80.4% utility gain in networks with low, medium and high levels of interference; maybe more importantly, we illustrate how the global network behavior can be controlled by modifying a few lines of code on a centralized abstraction.

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Section: Wnos Architecturementioning

confidence: 99%

WNOS: Enabling Principled Software-Defined Wireless Networking

Guan

Bertizzolo

Demirors

et al. 2021

IEEE/ACM Trans. Networking

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“…The authors in [15], [16] propose to solve the NUM problem with ADMM. Compared with the approaches in [15], [16], we adopt a different utility function to facilitate our multi-objective optimization problem and also use a different splitting method on the decision variables. Specifically, by introducing the following convex indicator function of link capacity constraints given by…”

Section: A Admm For Nummentioning

confidence: 99%

Joint Bandwidth Allocation and Path Selection in WANs with Path Cardinality Constraints

Zhang¹,

Xie²,

Zhang³

et al. 2020

Preprint

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In this paper, we study a joint bandwidth allocation and path selection problem via solving a multi-objective minimization problem under the path cardinality constraints, namely MOPC. Our problem formulation captures various types of objectives including the proportional fairness, the total completion time, as well as the worst-case link utilization ratio. Such an optimization problem is very challenging since it is highly non-convex. Almost all existing works deal with such a problem using relaxation techniques to transform it to be a convex optimization problem. However, we provide a novel solution framework based on the classic alternating direction method of multipliers (ADMM) approach for solving this problem. Our proposed algorithm is simple and easy to be implemented. Each step of our algorithm consists of either finding the maximal root of a single-cubic equation which is guaranteed to have at least one positive solution or solving a one-dimensional convex subproblem in a fixed interval. Under some mild assumptions, we prove that any limiting point of the generated sequence under our proposed algorithm is a stationary point. Extensive numerical simulations are performed to demonstrate the advantages of our algorithm compared with various baselines.

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“…This convergence speed can be improved to O(d/ε) by using an alternating direction method of multipliers (ADMM) approach [1,8]. ADMM updates are relatively cheap, but the method requires additional assumptions on the NUM objective (viz.…”

Section: B Relation To Existing Workmentioning

confidence: 99%

Large-Scale Network Utility Maximization: Countering Exponential Growth with Exponentiated Gradients

Vigneri¹,

Paschos

Mertikopoulos

2019

IEEE INFOCOM 2019 - IEEE Conference on Computer Communications

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Network utility maximization (NUM) is an iconic problem in network traffic management which is at the core of many current and emerging network design paradigms-and, in particular, software-defined networks (SDNs). Thus, given the exponential growth of modern-day networks (in both size and complexity), it is crucial to develop scalable algorithmic tools that are capable of providing efficient solutions in time which is dimension-free, i.e., independent-or nearly-independent-on the size of the system. To do so, we leverage a suite of modified gradient methods known as "mirror descent", and we derive a scalable and efficient algorithm for the NUM problem based on gradient exponentiation. We show that the convergence speed of the proposed algorithm only carries a logarithmic dependence on the size of the network, so it can be implemented reliably and efficiently in massively large networks where traditional gradient methods are prohibitively slow. These theoretical results are subsequently validated by extensive numerical simulations showing an improvement of several order of magnitudes over standard gradient methods in large-scale networks.

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Centralized network utility maximization over aggregate flows

Cited by 9 publications

References 20 publications

WNOS: Enabling Principled Software-Defined Wireless Networking

WNOS: Enabling Principled Software-Defined Wireless Networking

Joint Bandwidth Allocation and Path Selection in WANs with Path Cardinality Constraints

Large-Scale Network Utility Maximization: Countering Exponential Growth with Exponentiated Gradients

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