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无线传感器网络中的数据采集技术:一种跨层视角。

Data Gathering Techniques in WSN: A Cross-Layer View.

机构信息

School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

出版信息

Sensors (Basel). 2022 Mar 30;22(7):2650. doi: 10.3390/s22072650.

DOI:10.3390/s22072650
PMID:35408263
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9002776/
Abstract

Wireless sensor networks (WSNs) have taken a giant leap in scale, expanding their applicability to a large variety of technological domains and applications, ranging from the Internet of things (IoT) for smart cities and smart homes to wearable technology healthcare applications, underwater, agricultural and environmental monitoring and many more. This expansion is rapidly growing every passing day in terms of the variety, heterogeneity and the number of devices which such applications support. Data collection is commonly the core application in WSN and IoT networks, which are typically composed of a large variety of devices, some constrained by their resources (e.g., processing, storage, energy) and some by highly diverse demands. Many challenges span all the conceptual communication layers, from the Physical to the Applicational. Many novel solutions devised in the past do not scale well with the exponential growth in the population of the devices and need to be adapted, revised, or new innovative solutions are required to comply with this massive growth. Furthermore, recent technological advances present new opportunities which can be leveraged in this context. This paper provides a cross-layer perspective and review of data gathering in WSN and IoT networks. We provide some background and essential milestones that have laid the foundation of many subsequent solutions suggested over the years. We mainly concentrate on recent state-of-the-art research, which facilitates the scalable, energy-efficient, cost-effective, and human-friendly functionality of WSNs and the novel applications in the years to come.

摘要

无线传感器网络 (WSN) 在规模上取得了巨大飞跃,将其应用扩展到了各种技术领域和应用,从物联网 (IoT) 应用于智慧城市和智能家居,到可穿戴技术医疗保健应用、水下、农业和环境监测等等。这种扩展在各种设备的数量、多样性和异构性方面每天都在迅速增长。数据收集通常是 WSN 和 IoT 网络的核心应用,这些网络通常由各种设备组成,其中一些设备受到资源(例如处理、存储、能源)的限制,而另一些设备则受到高度多样化的需求的限制。许多挑战跨越了所有概念通信层,从物理层到应用层。过去设计的许多新颖解决方案不能很好地适应设备数量的指数级增长,需要进行调整、修改或需要新的创新解决方案来满足这种大规模增长。此外,最近的技术进步带来了新的机遇,可以在这种情况下加以利用。本文提供了一个跨层视角,对 WSN 和 IoT 网络中的数据收集进行了回顾。我们提供了一些背景和重要的里程碑,这些里程碑为多年来提出的许多后续解决方案奠定了基础。我们主要集中在最新的最先进的研究上,这些研究促进了 WSN 的可扩展、节能、具有成本效益和人性化的功能,以及未来几年的新应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/5b6dfee1bc3f/sensors-22-02650-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/32a80ab35d27/sensors-22-02650-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/4f15ec63031d/sensors-22-02650-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/1a718e5ef90e/sensors-22-02650-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/98a9b4e3f8cb/sensors-22-02650-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/5b6dfee1bc3f/sensors-22-02650-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/32a80ab35d27/sensors-22-02650-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/4f15ec63031d/sensors-22-02650-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/1a718e5ef90e/sensors-22-02650-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/98a9b4e3f8cb/sensors-22-02650-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7e7/9002776/5b6dfee1bc3f/sensors-22-02650-g005.jpg

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