Nonconvex integer optimal robust impulsive control strategy for first-order piecewise finite precision nonlinear random early detection algorithm

There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for characterizing the average queue size of the random early detection (RED) algorithm. Second, this paper proposes a nonconvex integer optimal robust impuls...

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Published inISA transactions Vol. 51; no. 3; pp. 439 - 445
Main Authors Yuk-Fan Ho, Charlotte, Wing-Kuen Ling, Bingo, Iu, Herbert H.C., Fernando, Tyrone L.
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 01.05.2012
Elsevier
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Online AccessGet full text
ISSN0019-0578
1879-2022
1879-2022
DOI10.1016/j.isatra.2011.11.007

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Abstract There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for characterizing the average queue size of the random early detection (RED) algorithm. Second, this paper proposes a nonconvex integer optimal robust impulsive control strategy for stabilizing the average queue size. The objective of the control strategy is to determine the average queue size so that the average power of the impulsive control force is minimized subject to a constraint on the absolute difference between the actual average queue size and the theoretical average queue size at the equilibrium point. Computer numerical simulation results show that the proposed control strategy is effective and efficient for stabilizing the average queue size. ► We investigate random early detection (RED) algorithm for Internet traffic control. ► We develop a nonconvex integer optimal robust impulsive control strategy for chaotic systems. ► We develop a first-order piecewise finite precision nonlinear dynamical model for the RED algorithm.
AbstractList There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for characterizing the average queue size of the random early detection (RED) algorithm. Second, this paper proposes a nonconvex integer optimal robust impulsive control strategy for stabilizing the average queue size. The objective of the control strategy is to determine the average queue size so that the average power of the impulsive control force is minimized subject to a constraint on the absolute difference between the actual average queue size and the theoretical average queue size at the equilibrium point. Computer numerical simulation results show that the proposed control strategy is effective and efficient for stabilizing the average queue size.
There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for characterizing the average queue size of the random early detection (RED) algorithm. Second, this paper proposes a nonconvex integer optimal robust impulsive control strategy for stabilizing the average queue size. The objective of the control strategy is to determine the average queue size so that the average power of the impulsive control force is minimized subject to a constraint on the absolute difference between the actual average queue size and the theoretical average queue size at the equilibrium point. Computer numerical simulation results show that the proposed control strategy is effective and efficient for stabilizing the average queue size. ► We investigate random early detection (RED) algorithm for Internet traffic control. ► We develop a nonconvex integer optimal robust impulsive control strategy for chaotic systems. ► We develop a first-order piecewise finite precision nonlinear dynamical model for the RED algorithm.
There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for characterizing the average queue size of the random early detection (RED) algorithm. Second, this paper proposes a nonconvex integer optimal robust impulsive control strategy for stabilizing the average queue size. The objective of the control strategy is to determine the average queue size so that the average power of the impulsive control force is minimized subject to a constraint on the absolute difference between the actual average queue size and the theoretical average queue size at the equilibrium point. Computer numerical simulation results show that the proposed control strategy is effective and efficient for stabilizing the average queue size.There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for characterizing the average queue size of the random early detection (RED) algorithm. Second, this paper proposes a nonconvex integer optimal robust impulsive control strategy for stabilizing the average queue size. The objective of the control strategy is to determine the average queue size so that the average power of the impulsive control force is minimized subject to a constraint on the absolute difference between the actual average queue size and the theoretical average queue size at the equilibrium point. Computer numerical simulation results show that the proposed control strategy is effective and efficient for stabilizing the average queue size.
Author Wing-Kuen Ling, Bingo
Yuk-Fan Ho, Charlotte
Fernando, Tyrone L.
Iu, Herbert H.C.
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crossref_primary_10_1049_iet_spr_2020_0199
Cites_doi 10.1109/TNET.2004.838600
10.1142/S0218127408021816
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Issue 3
Keywords First-order piecewise finite precision nonlinear dynamical model
Nonconvex integer optimal robust impulsive control
Random early detection algorithm
Computer simulation
Control synthesis
Impulse control
Equilibrium point
Robust control
Queue length
Optimal strategy
Power control
Optimal control
Traffic management
Non linear model
Force control
Optimal control (mathematics)
Random early detection protocol
Non convex analysis
Language English
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Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.
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Snippet There are two main contributions of this paper. First, this paper proposes a first-order piecewise finite precision nonlinear dynamical model for...
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SubjectTerms Adaptative systems
Algorithms
Applied sciences
Computer science; control theory; systems
Computer simulation
Computer systems and distributed systems. User interface
Control system synthesis
Control theory. Systems
Exact sciences and technology
First-order piecewise finite precision nonlinear dynamical model
Mathematical analysis
Mathematical models
Nonconvex integer optimal robust impulsive control
Nonlinearity
Optimal control
Optimization
Queues
Random early detection algorithm
Software
Strategy
Title Nonconvex integer optimal robust impulsive control strategy for first-order piecewise finite precision nonlinear random early detection algorithm
URI https://dx.doi.org/10.1016/j.isatra.2011.11.007
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