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Hierarchical Optimal Control Method for Controlling Large-Scale Self-Organizing Networks

Published: 27 October 2017 Publication History

Abstract

Self-organization has the potential for high scalability, adaptability, flexibility, and robustness, which are vital features for realizing future networks. The convergence of self-organizing control, however, is slow in some practical applications in comparison with control by conventional deterministic systems using global information. It is therefore important to facilitate the convergence of self-organizing controls. In controlled self-organization, which introduces an external controller into self-organizing systems, the network is controlled to guide systems to a desired state. Although existing controlled self-organization schemes could achieve the same state, it is difficult for an external controller to collect information about the network and to provide control inputs to the network, especially when the network size is large. This is because the computational cost for designing the external controller and for calculating the control inputs increases rapidly as the number of nodes in the network becomes large. Therefore, we partition a network into several sub-networks and introduce two types of controllers, a central controller and several sub-controllers that control the network in a hierarchical manner. In this study, we propose a hierarchical optimal feedback mechanism for self-organizing systems and apply this mechanism to potential-based self-organizing routing. Simulation results show that the proposed mechanism improves the convergence speed of potential-field construction (i.e., route construction) up to 10.6-fold with low computational and communication costs.

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  • (2021)Adaptive Information Sharing with Ontological Relevance Computation for Decentralized Self-Organization SystemsEntropy10.3390/e2303034223:3(342)Online publication date: 14-Mar-2021

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  1. Hierarchical Optimal Control Method for Controlling Large-Scale Self-Organizing Networks

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    cover image ACM Transactions on Autonomous and Adaptive Systems
    ACM Transactions on Autonomous and Adaptive Systems  Volume 12, Issue 4
    December 2017
    224 pages
    ISSN:1556-4665
    EISSN:1556-4703
    DOI:10.1145/3155314
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 27 October 2017
    Accepted: 01 July 2017
    Revised: 01 March 2017
    Received: 01 September 2015
    Published in TAAS Volume 12, Issue 4

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    Author Tags

    1. Controlled self-organization
    2. fast convergence
    3. hierarchical robust control
    4. potential-based routing

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    • a Grant-in-Aid for Scientific Research (B) from JSPS in Japan
    • a Grant-in-Aid for Young Scientist (Start-up) of the Japan Society for the Promotion of Science (JSPS) in Japan

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    • (2021)Adaptive Information Sharing with Ontological Relevance Computation for Decentralized Self-Organization SystemsEntropy10.3390/e2303034223:3(342)Online publication date: 14-Mar-2021

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