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A Small World Phenomenon Based Greedy Network Model for Robust IoT Network

机译:基于小型世界现象的鲁棒IOT网络贪婪网络模型

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摘要

The ongoing evolution of the Internet of Things (IoT) empowers the Internet, which is progressively transforming the technology. The robustness plays a crucial role in the constrained lightweight IoT network. The key requirement includes an optimized model to ensure robustness and resilience towards the failure of a node as well as the complete sensor IoT network. The proposed technique uses two greedy criteria that improve the robustness of IoT networks. The proposed method utilizes the widely known Mahalanobis distance model to find out the shortcuts. This scheme also presents the concept of the regional influence of a node to optimize the topology of the network. Additionally, this scheme also presented algorithms for shortcut additions between high powered sensor nodes (HPSN) and the sink. Finally, this paper evaluates the performance of the proposed scheme in-terms of clustering coefficient, average path length, and the network latency, compared to existing techniques.
机译:事情的持续演变(物联网)赋予互联网,这逐步改造了该技术。鲁棒性在受限的轻量级IOT网络中起着至关重要的作用。关键要求包括优化的模型,以确保稳健性和恢复能力朝向节点的失败以及完整的传感器IOT网络。所提出的技术使用了两个贪婪标准,提高了IOT网络的稳健性。所提出的方法利用广泛的已知的Mahalanobis距离模型来找出快捷方式。该方案还提出了节点区域影响的概念,以优化网络的拓扑。另外,该方案还提出了用于在高功率传感器节点(HPSN)和接收器之间的快捷方式添加的算法。最后,与现有技术相比,本文评估了群集系数,平均路径长度和网络延迟的提出方案的性能。

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