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Optimal Balanced Coordinated Network Resource Allocation Using Swarm Optimization.

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Title: Optimal Balanced Coordinated Network Resource Allocation Using Swarm Optimization.
Authors: Hui, Qing1, Zhang, Haopeng1
Source: IEEE Transactions on Systems, Man & Cybernetics. Systems. May2015, Vol. 45 Issue 5, p770-787. 18p.
Subject Terms: *RESOURCE allocation, *OPTIMAL control theory, LINEAR systems, LOAD balancing (Computer networks), MULTIAGENT systems, NONCONVEX programming, SWARM intelligence
Abstract: In this paper, we present a new control-theoretic framework to efficiently design balanced coordinated resource allocation algorithms in a network based on semistabilization theory for discrete-time stochastic linear systems together with compartmental modeling. Specifically, necessary and sufficient conditions for equivalent, control-theoretic characterizations of the proposed balanced coordinated resource allocation design problem are derived, which are based on a new notion of semiobservability and a new semistable Lyapunov equation. With this theory, we first unveil a striking connection between the balanced coordinated network resource allocation design problem and optimal semistable control theory by means of a stochastic optimal semistable control technique. Then we convert this optimal control-based design problem into a constrained, nonlinear optimization problem to look for possible numerical solutions to the original balanced coordinated resource allocation algorithm design problem. To this end, we propose a class of randomized swarm optimization-based numerical algorithms called multiagent coordination optimization to solve the constrained, nonlinear optimization problem. Finally, numerical results are provided to validate the proposed design framework and an application of a target search problem for threat detection and resource allocation is presented to further show the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Transactions on Systems, Man & Cybernetics. Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: In this paper, we present a new control-theoretic framework to efficiently design balanced coordinated resource allocation algorithms in a network based on semistabilization theory for discrete-time stochastic linear systems together with compartmental modeling. Specifically, necessary and sufficient conditions for equivalent, control-theoretic characterizations of the proposed balanced coordinated resource allocation design problem are derived, which are based on a new notion of semiobservability and a new semistable Lyapunov equation. With this theory, we first unveil a striking connection between the balanced coordinated network resource allocation design problem and optimal semistable control theory by means of a stochastic optimal semistable control technique. Then we convert this optimal control-based design problem into a constrained, nonlinear optimization problem to look for possible numerical solutions to the original balanced coordinated resource allocation algorithm design problem. To this end, we propose a class of randomized swarm optimization-based numerical algorithms called multiagent coordination optimization to solve the constrained, nonlinear optimization problem. Finally, numerical results are provided to validate the proposed design framework and an application of a target search problem for threat detection and resource allocation is presented to further show the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]
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  Data: <i>Copyright of IEEE Transactions on Systems, Man & Cybernetics. Systems is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/TSMC.2014.2371871
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 770
    Subjects:
      – SubjectFull: RESOURCE allocation
        Type: general
      – SubjectFull: OPTIMAL control theory
        Type: general
      – SubjectFull: LINEAR systems
        Type: general
      – SubjectFull: LOAD balancing (Computer networks)
        Type: general
      – SubjectFull: MULTIAGENT systems
        Type: general
      – SubjectFull: NONCONVEX programming
        Type: general
      – SubjectFull: SWARM intelligence
        Type: general
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      – TitleFull: Optimal Balanced Coordinated Network Resource Allocation Using Swarm Optimization.
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            NameFull: Hui, Qing
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            NameFull: Zhang, Haopeng
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            – D: 01
              M: 05
              Text: May2015
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              Y: 2015
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