An Architecture for Managing Internet of Things based on Cognitive Peer-to-peer Networks

Mahdi Ghorbani, M. Meybodi, Ali Mohammad Saghiri
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Abstract

Peer-to-peer systems are well-known patterns of distributed systems which created several revelations in designing ultra-scalable systems. Recently, these types of systems are evolved into cognitive peer-to-peer networks. Because of the distributed nature of Internet of Things (IoT), peer-to-peer systems such as blockchain can be used to design management mechanisms in IoT. Therefore, we need an architecture which facilitates the utilization of peer-to-peer systems in IoT based systems. To the best of our knowledge, there is no general architecture based on cognitive peer-to-peer networks. Therefore, in this paper, we propose an architecture for managing IoT based on cognitive peer-to-peer networks. In order to study the potential of the proposed architecture, we suggest an adaptive search mechanism and also a topology management algorithm utilizing the proposed architecture. The results show the efficiency of the suggested algorithms. The proposed architecture may facilitate a new evolution from peer-to-peer systems to thing-to-thing systems.
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基于认知点对点网络的物联网管理体系结构
点对点系统是众所周知的分布式系统模式,它为设计超可扩展系统提供了一些启示。最近,这些类型的系统演变为认知点对点网络。由于物联网(IoT)的分布式特性,区块链等点对点系统可用于设计物联网中的管理机制。因此,我们需要一种便于在基于物联网的系统中使用点对点系统的架构。据我们所知,目前还没有基于认知点对点网络的通用架构。因此,在本文中,我们提出了一种基于认知对等网络的物联网管理架构。为了研究该架构的潜力,我们提出了一种自适应搜索机制和一种利用该架构的拓扑管理算法。实验结果表明了所提算法的有效性。所提出的体系结构可能促进从点对点系统到物对物系统的新演变。
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