社会物联网(SIoT)网络的可控性方法

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zahra Aghaee , Afsaneh Fatemi , Peyman Arebi
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引用次数: 0

摘要

近年来,一种名为社会物联网(SIoT)的复杂网络引起了研究人员的关注。可控性是复杂网络的重要问题之一,在社会、生物和技术网络中都有重要应用。应用这一问题在社会智慧城市的控制中也能发挥重要作用,但它尚未被定义为 SIoT 的一个具体问题,也没有提供解决方案。本文探讨了时空 SIoT 网络的可控性问题。首先,本文给出了时空 SIoT 网络的定义。然后,对该网络的独特关系进行正式定义和建模。接下来,将可控性问题应用于时态 SIoT 网络(CSIoT),以确定最小驱动节点集(MDS)。然后,将提出的 CSIoT 与最先进的性能分析方法进行比较。在所得结果中,对异质性(不同类型、品牌和型号)进行了调查。此外,在 152 个不同的集合中,69.80% 的 SIoT 子图节点被确定为关键驱动节点。所提出的可控性以分布式方式处理网络控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A controllability method on the social Internet of Things (SIoT) network
In recent years, one type of complex network called the Social Internet of Things (SIoT) has attracted the attention of researchers. Controllability is one of the important problems in complex networks and it has essential applications in social, biological, and technical networks. Applying this problem can also play an important role in the control of social smart cities, but it has not yet been defined as a specific problem on SIoT, and no solution has been provided for it. This paper addresses the controllability problem of the temporal SIoT network. In this regard, first, a definition for the temporal SIoT network is provided. Then, the unique relationships of this network are defined and modeled formally. In the following, the Controllability problem is applied to the temporal SIoT network (CSIoT) to identify the Minimum Driver nodes Set (MDS). Then proposed CSIoT is compared with the state-of-the-art methods for performance analysis. In the obtained results, the heterogeneity (different types, brands, and models) has been investigated. Also, 69.80 % of the SIoT sub-graphs nodes have been identified as critical driver nodes in 152 different sets. The proposed controllability deals with network control in a distributed manner.
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来源期刊
Pervasive and Mobile Computing
Pervasive and Mobile Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
7.70
自引率
2.30%
发文量
80
审稿时长
68 days
期刊介绍: As envisioned by Mark Weiser as early as 1991, pervasive computing systems and services have truly become integral parts of our daily lives. Tremendous developments in a multitude of technologies ranging from personalized and embedded smart devices (e.g., smartphones, sensors, wearables, IoTs, etc.) to ubiquitous connectivity, via a variety of wireless mobile communications and cognitive networking infrastructures, to advanced computing techniques (including edge, fog and cloud) and user-friendly middleware services and platforms have significantly contributed to the unprecedented advances in pervasive and mobile computing. Cutting-edge applications and paradigms have evolved, such as cyber-physical systems and smart environments (e.g., smart city, smart energy, smart transportation, smart healthcare, etc.) that also involve human in the loop through social interactions and participatory and/or mobile crowd sensing, for example. The goal of pervasive computing systems is to improve human experience and quality of life, without explicit awareness of the underlying communications and computing technologies. The Pervasive and Mobile Computing Journal (PMC) is a high-impact, peer-reviewed technical journal that publishes high-quality scientific articles spanning theory and practice, and covering all aspects of pervasive and mobile computing and systems.
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