Alternative Distributed Algorithms for Network Utility Maximization: Framework and Applications

Network utility maximization (NUM) problem formulations provide an important approach to conduct network resource allocation and to view layering as optimization decomposition. In the existing literature, distributed implementations are typically achieved by means of the so-called dual decomposition...

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Veröffentlicht in:IEEE transactions on automatic control Jg. 52; H. 12; S. 2254 - 2269
Hauptverfasser: Palomar, D.P., Mung Chiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.12.2007
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Allocations
Applied sciences
Architecture
Computer architecture
Computer science; control theory; systems
Congestion control
Control system synthesis
Control theory. Systems
Convergence
Decomposition
distributed algorithm
Distributed algorithms
Distributed computing
Distributed control
Exact sciences and technology
Mathematical analysis
Mathematical models
mathematical programming/optimization
Maximization
Message passing
network control by pricing
network utility maximization (NUM)
Networks
Protocols
rate control
resource allocation
Resource management
Routing
Studies
Utility programs
Enumeration
Maximization
Resource allocation
Network architecture
Control synthesis
Routing
network control by pricing
Congestion control
Constrained optimization
Control constraint
Distributed algorithm
Pricing
Distributed control
rate control
mathematical programming/optimization
Service quality
Traffic congestion
Message transmission
network utility maximization (NUM)
Mathematical programming
ISSN:0018-9286, 1558-2523
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Beschreibung
Zusammenfassung:Network utility maximization (NUM) problem formulations provide an important approach to conduct network resource allocation and to view layering as optimization decomposition. In the existing literature, distributed implementations are typically achieved by means of the so-called dual decomposition technique. However, the span of decomposition possibilities includes many other elements that, thus far, have not been fully exploited, such as the use of the primal decomposition technique, the versatile introduction of auxiliary variables, and the potential of multilevel decompositions. This paper presents a systematic framework to exploit alternative decomposition structures as a way to obtain different distributed algorithms, each with a different tradeoff among convergence speed, message passing amount and asymmetry, and distributed computation architecture. Several specific applications are considered to illustrate the proposed framework, including resource-constrained and direct-control rate allocation, and rate allocation among QoS classes with multipath routing. For each of these applications, the associated generalized NUM formulation is first presented, followed by the development of novel alternative decompositions and numerical experiments on the resulting new distributed algorithms. A systematic enumeration and comparison of alternative vertical decompositions in the future will help complete a mathematical theory of network architectures.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2007.910665