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RDSC:物联网网络中基于范围的设备空间聚类

RDSC: Range-Based Device Spatial Clustering for IoT Networks.

作者信息

Achkouty Fouad, Gallon Laurent, Chbeir Richard

机构信息

OpenCEMS, LIUPPA, E2S UPPA, University Pau & Pays Adour, 64600 Anglet, France.

OpenCEMS, LIUPPA, E2S UPPA, University Pau & Pays Adour, 40000 Mont de Marsan, France.

出版信息

Sensors (Basel). 2024 Sep 9;24(17):5851. doi: 10.3390/s24175851.

Abstract

The growth of the Internet of Things (IoT) has become a crucial area of modern research. While the increasing number of IoT devices has driven significant advancements, it has also introduced several challenges, such as data storage, data privacy, communication protocols, complex network topologies, and IoT device management. In essence, the management of IoT devices is becoming more and more challenging, especially with the limited capacity and power of the IoT devices. The devices, having limited capacities, cannot store the information of the entire environment at once. In addition, device power consumption can affect network performance and stability. The devices' sensing areas with device grouping and management can simplify further networking tasks and improve response quality with data aggregation and correction techniques. In fact, most research papers are looking forward to expanding network lifetimes by relying on devices with high power capabilities. This paper proposes a device spatial clustering technique that covers crucial challenges in IoT. Our approach groups the dispersed devices to create clusters of connected devices while considering their coverage, their storage capacities, and their power. A new clustering protocol alongside a new clustering algorithm is introduced, resolving the aforementioned challenges. Moreover, a technique for non-sensed area extraction is presented. The efficiency of the proposed approach has been evaluated with extensive experiments that gave notable results. Our technique was also compared with other clustering algorithms, showing the different results of these algorithms.

摘要

物联网(IoT)的发展已成为现代研究的一个关键领域。虽然物联网设备数量的增加推动了显著的进步,但它也带来了一些挑战,如数据存储、数据隐私、通信协议、复杂的网络拓扑结构以及物联网设备管理。从本质上讲,物联网设备的管理正变得越来越具有挑战性,尤其是考虑到物联网设备有限的容量和功率。这些设备容量有限,无法一次性存储整个环境的信息。此外,设备功耗会影响网络性能和稳定性。通过设备分组和管理来划分设备的传感区域,可以利用数据聚合和校正技术简化进一步的网络任务并提高响应质量。事实上,大多数研究论文都期望依靠具有高功率能力的设备来延长网络寿命。本文提出了一种解决物联网中关键挑战的设备空间聚类技术。我们的方法在考虑设备的覆盖范围、存储容量和功率的同时,将分散的设备进行分组,以创建连接设备的集群。引入了一种新的聚类协议和一种新的聚类算法,解决了上述挑战。此外,还提出了一种非传感区域提取技术。通过大量实验对所提方法的效率进行了评估,实验结果显著。我们的技术还与其他聚类算法进行了比较,展示了这些算法的不同结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b29b/11398043/a97df97a80b4/sensors-24-05851-g001.jpg

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