针对具有自适应拓扑的不同类型网络的基于图的自调节功能

IF 0.6 Q4 AUTOMATION & CONTROL SYSTEMS

AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-02-29 DOI:10.3103/S0146411623080217

E. Yu. Pavlenko, M. A. Pakhomov

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引用次数: 0

摘要

摘要-本文介绍了基于图论的自适应网络拓扑网络自我调节方法。这些方法仅限于无节点移动性的网络--点对点网络和异构传感器网络，以及以智能电网智能能耗网络为例的工业网络。针对每种网络类型，都描述了广义的目标函数，提出了自我调节的条件，并对自我调节过程进行了正式描述。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Graph-Based Self-Regulation for Different Types of Networks with Adaptive Topology

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Graph-Based Self-Regulation for Different Types of Networks with Adaptive Topology

This article presents graph theory-based approaches to self-regulation of networks with adaptive network topology. These approaches are limited to networks with no node mobility—peer-to-peer and heterogeneous sensor networks, as well as industrial networks on the example of Smart Grid smart energy consumption networks. For each network type, a generalized target function is described, conditions for self-regulation are formulated, and a formal description of the process of self-regulation is provided.

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来源期刊

AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.70

自引率

22.20%

发文量

期刊介绍： Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision