A Low-Cost and Infrastructure-Less LoRa Wireless Network Testbed for Cognitive Internet of Things

IF 7 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2024-09-16 DOI:10.1109/TCCN.2024.3461671
Ye Liu;Pei Tian;Carlo Alberto Boano;Xiaoyuan Ma;Qing Yang;Honggang Wang
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Abstract

Low-power wide area network (LPWAN) testbeds are essential for cognitive communications and networking, as they provide practical and controlled environments for testing, validating, and advancing cognitive technologies in the cognitive Internet of Things (IoT). However, establishing extensive outdoor testbeds faces a significant challenge due to the lack of robust infrastructure, limiting testing to indoor settings or a small number of devices. This constraint prevents adequate testing of cognitive communications and networking techniques. In this article, we introduce ChirpBox: an innovative, infrastructure-free, and cost-effective LPWAN testbed that revolutionizes the utilization of LoRa nodes. Beyond their conventional role in experimentation, these nodes in ChirpBox orchestrate all operations, from disseminating firmware for testing to collecting log traces at the conclusion of each test cycle. This holistic approach is enabled by our development of an all-to-all multi-channel protocol that leverages concurrent transmissions for efficient communication across multi-hop LoRa networks. Following a detailed presentation of ChirpBox’s design and implementation, we demonstrate its capabilities through a practical deployment. This evaluation offers experimental insights into the testbed’s performance, illustrating its operations and highlighting its potential to advance cognitive IoT research and development.
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用于认知物联网的低成本、无基础设施 LoRa 无线网络试验台
低功耗广域网(LPWAN)测试平台对于认知通信和网络至关重要,因为它们为认知物联网(IoT)中的认知技术的测试、验证和推进提供了实用和可控的环境。然而,由于缺乏强大的基础设施,限制了室内环境或少量设备的测试,建立广泛的室外测试平台面临着重大挑战。这种限制阻碍了对认知通信和网络技术的充分测试。在本文中,我们将介绍ChirpBox:一种创新的、无基础设施的、具有成本效益的LPWAN测试平台,它彻底改变了LoRa节点的利用率。除了它们在实验中的传统角色之外,ChirpBox中的这些节点编排了所有操作,从分发测试固件到在每个测试周期结束时收集日志痕迹。这种整体方法是通过我们开发的全对全多通道协议实现的,该协议利用并发传输实现跨多跳LoRa网络的高效通信。在详细介绍ChirpBox的设计和实现之后,我们通过实际部署演示其功能。该评估提供了对测试平台性能的实验见解,说明了其操作,并强调了其推进认知物联网研究和开发的潜力。
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来源期刊
IEEE Transactions on Cognitive Communications and Networking
IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence
CiteScore
15.50
自引率
7.00%
发文量
108
期刊介绍: The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.
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