A Survey on the Progress of Testing Techniques and Methods for Wireless Sensor Networks

Wu, Jingjing; Jiang, Wenxian; Mei, Yaxin; Zhou, Yaqin; Wang, Tian

doi:10.1109/access.2018.2887246

Cited by 10 publications

(5 citation statements)

References 41 publications

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“…The system architecture and design criteria for real-world applications such as health and environmental monitoring were evaluated in relation to the WSN testbed. Several researchers have highlighted key testbed elements that can be customized to design specifications, such as hardware deployment capabilities [10][11][12][13][14]. Some researchers have emphasized the use of different hardware components such as Raspberry Pi and Arduino [15], as well as use cases such as sensor node distribution for environmental applications.…”

Section: Related Workmentioning

confidence: 99%

A Novel SDWSN-Based Testbed for IoT Smart Applications

Al-Hamid,

Karegar,

Chong

2023

Future Internet

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Wireless sensor network (WSN) environment monitoring and smart city applications present challenges for maintaining network connectivity when, for example, dynamic events occur. Such applications can benefit from recent technologies such as software-defined networks (SDNs) and network virtualization to support network flexibility and offer validation for a physical network. This paper aims to present a testbed-based, software-defined wireless sensor network (SDWSN) for IoT applications with a focus on promoting the approach of virtual network testing and analysis prior to physical network implementation to monitor and repair any network failures. Herein, physical network implementation employing hardware boards such as Texas Instruments CC2538 (TI CC2538) and TI CC1352R sensor nodes is presented and designed based on virtual WSN- based clustering for stationary and dynamic networks use cases. The key performance indicators such as evaluating node (such as a gateway node to the Internet) connection capability based on packet drop and energy consumption virtually and physically are discussed. According to the test findings, the proposed software-defined physical network benefited from “prior-to-implementation” analysis via virtualization, as the performance of both virtual and physical networks is comparable.

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Section: Related Workmentioning

confidence: 99%

A Novel SDWSN-Based Testbed for IoT Smart Applications

Al-Hamid,

Karegar,

Chong

2023

Future Internet

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“…Test automation frameworks and testbeds, specifically focusing on interoperability and integration testing, are discussed in several studies. Wu et al summarized currently available approaches to test Wireless Sensor Networks (WSNs) and include integration testing in their discussion [13]. However, the study is not exhaustive, as other possible approaches can be identified and employed.…”

Section: Related Workmentioning

confidence: 99%

PatrIoT: IoT Automated Interoperability and Integration Testing Framework

Bureš¹,

Ahmed²,

Rechtberger³

et al. 2021

Preprint

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With the rapid growth of the contemporary Internet of Things (IoT) market, the established systems raise a number of concerns regarding the reliability and the potential presence of critical integration defects. In this paper, we present a PatrIoT framework that aims to provide flexible support to construct an effective IoT system testbed to implement automated interoperability and integration testing. The framework allows scaling from a pure physical testbed to a simulated environment using a number of predefined modules and elements to simulate an IoT device or part of the tested infrastructure. PatrIoT also contains a set of reference example testbeds and several sets of example automated tests for a smart street use case.

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“…Wireless networks (WNs), as a kind of new information and communication network, connect the physical systems to cyber worlds. In addition, WNs have gained widespread application in IoT including healthcare, public safety, agriculture, and retail due to their low power consumption, flexible networking, unlimited potential, and relevant other features [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Control of Malware Propagation in Wireless IoT Networks

Yan

Song²,

Zhang

et al. 2021

Security and Communication Networks

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Wireless Internet of Things (IoT) devices densely populate our daily life, but also attract many attackers to attack them. In this paper, we propose a new Heterogeneous Susceptible-Exposed-Infected-Recovered (HSEIR) epidemic model to characterize the effect of heterogeneity of infected wireless IoT devices on malware spreading. Based on the proposed model, we obtain the basic reproduction number, which represents the threshold value of diffusion and governs that the malware is diffusion or not. Also, we derive the malware propagation scale under different cases. These analyses provide theoretical guidance for the application of defense techniques. Numerical simulations validated the correctness and effectiveness of theoretical results. Then, by using Pontryagin’s Minimum Principle, optimal control strategy is proposed to seek time-varying cost-effective solutions against malware outbreaks. More numerical results also showed that some control strategies, such as quarantine and vaccination, should be taken at the beginning of the malware outbreak immediately and become less necessary after a certain period. However, the repairing and fixing strategy, for example applying antivirus patches, would be keep on going constantly.

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A Survey on the Progress of Testing Techniques and Methods for Wireless Sensor Networks

Cited by 10 publications

References 41 publications

A Novel SDWSN-Based Testbed for IoT Smart Applications

A Novel SDWSN-Based Testbed for IoT Smart Applications

PatrIoT: IoT Automated Interoperability and Integration Testing Framework

Modeling and Control of Malware Propagation in Wireless IoT Networks

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