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1. Enabling Cross-technology Communication from LoRa to ZigBee via Payload Encoding in Sub-1 GHz Bands

   https://doi.org/10.1145/3470452  

   Shi, Junyang; Mu, Di; Sha, Mo (February 2022, ACM Transactions on Sensor Networks)

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   Low-power wireless mesh networks (LPWMNs) have been widely used in wireless monitoring and control applications. Although LPWMNs work satisfactorily most of the time thanks to decades of research, they are often complex, inelastic to change, and difficult to manage once the networks are deployed. Moreover, the deliveries of control commands, especially those carrying urgent information such as emergency alarms, suffer long delay, since the messages must go through the hop-by-hop transport. Recent studies show that adding low-power wide-area network radios such as LoRa onto the LPWMN devices (e.g., ZigBee) effectively overcomes the limitation. However, users have shown a marked reluctance to embrace the new heterogeneous communication approach because of the cost of hardware modification. In this article, we introduce LoRaBee, a novel LoRa to ZigBee cross-technology communication (CTC) approach, which leverages the energy emission in the Sub-1 GHz bands as the carrier to deliver information. Although LoRa and ZigBee adopt distinct modulation techniques, LoRaBee sends information from LoRa to ZigBee by putting specific bytes in the payload of legitimate LoRa packets. The bytes are selected such that the corresponding LoRa chirps can be recognized by the ZigBee devices through sampling the received signal strength. Experimental results show that our LoRaBee provides reliable CTC communication from LoRa to ZigBee with the throughput of up to 281.61 bps in the Sub-1 GHz bands. 

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2. MERA: Meta-Learning Based Runtime Adaptation for Industrial Wireless Sensor-Actuator Networks

   https://doi.org/10.1145/3665330  

   Cheng, Xia; Sha, Mo (July 2024, ACM Transactions on Sensor Networks)

   IEEE 802.15.4-based industrial wireless sensor-actuator networks (WSANs) have been widely deployed to connect sensors, actuators, and controllers in industrial facilities. Configuring an industrial WSAN to meet the application-specified quality of service (QoS) requirements is a complex process, which involves theoretical computation, simulation, and field testing, among other tasks. Since industrial wireless networks become increasingly hierarchical, heterogeneous, and complex, many research efforts have been made to apply wireless simulations and advanced machine learning techniques for network configuration. Unfortunately, our study shows that the network configuration model generated by the state-of-the-art method decays quickly over time. To address this issue, we develop aMEta-learning basedRuntimeAdaptation (MERA) method that efficiently adapts network configuration models for industrial WSANs at runtime. Under MERA, the parameters of the network configuration model are explicitly trained such that a small number of optimization steps with only a few new measurements will produce good generalization performance after the network condition changes. We also develop a data sampling method to reduce the measurements required by MERA at runtime without sacrificing its performance. Experimental results show that MERA achieves higher prediction accuracy with less physical measurements, less computation time, and longer adaptation intervals compared to a state-of-the-art baseline. 

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3. Cybersecurity Analysis of an IEEE 802.15.4 based Wireless Sensor Network for Smart Grid Power Monitoring on a Naval Vessel

   Rivas Rey, Xaime; Halpin, Thomas; Hadgekar, Shantanu; Miu, Karen; Dandekar, Kapil R. (June 2018, ASNE Technology Systems and Ships (TSS))

   Most sensor networks on a naval vessel are wired directly to the control unit, and this includes the Power System. This paper demonstrates how an IEEE 802.15.4 based Wireless Sensor Network (WSN) could be used to have an easy to deploy, flexible and affordable Smart Grid Power System monitoring structure. In published literature, it has been qualitatively proven that a WSN can work on a ship, despite its more complex Radio Frequency (RF) environment. This work quantifies this, showing the achievable levels of Packet Error Rate under different levels of Signal to Interference and Noise Ratio, proving that it could be used instead of a wired channel. Another important aspect studied was the cybersecurity implications of using a wireless network versus a wired one. The effects of delayed, missing and faked power measurements were also done, along with a discussion of what could be done to detect and mitigate these effects. 

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4. Cybersecurity Analysis of an IEEE 802.15.4 based Wireless Sensor Network for Smart Grid Power Monitoring on a Naval Vessel

   Rivas Rey, Xaime; Halpin, Thomas; Hadgekar, Shantanu; Miu, Karen; Dandekar, Kapil R. (June 2018, ASNE Technology, Systems and Ships 2018)

   Most sensor networks on a naval vessel are wired directly to the control unit , and this includes the Power System. This paper demonstrates how an IEEE 802.15.4 based Wireless Sensor Network (WSN) could be used to have an easy to deploy, flexible and affordable Smart Grid Power System monitoring structure. In published literature, it has been qualitatively proven that a WSN can work on a ship, despite its more complex Radio Frequency (RF) environment. This work quantifies this, showing the achievable levels of Packet Error Rate under different levels of Signal to Interference and Noise Ratio, proving that it could be used instead of a wired channel. Another important aspect studied was the cybersecurity implications of using a wireless network versus a wired one. The effects of delayed, missing and faked power measurements were also done, along with a discussion of what could be done to detect and mitigate these effects. 

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5. Cybersecurity Analysis of an IEEE 802.15.4 Based Wireless Sensor Network for Smart Grid Power Monitoring on a Naval Vessel

   Rey, Xaime Rivas; Halpin, Thomas J.; Hadgekar, Shantanu; Miu, Karen; Dandekar, Kapil R. (January 2018, Naval engineers journal)

   Most sensor networks on a naval vessel are wired directly to the control unit,[1, 16] and this includes the Power System. This paper demonstrates how an IEEE 802.15.4 based Wireless Sensor Network (WSN) could be used to have an easy to deploy, flexible and affordable Smart Grid Power System monitoring structure. In published literature, it has been qualitatively proven that a WSN can work on a ship, despite its more complex Radio Frequency (RF) environment. This work quantifies this, showing the achievable levels of Packet Error Rate under different levels of Signal to Interference and Noise Ratio, proving that it could be used instead of a wired channel. Another important aspect studied was the cybersecurity implications of using a wireless network versus a wired one. The effects of delayed, missing and faked power measurements were also studied, along with a discussion of what could be done to detect and mitigate them. 

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