Mid Sweden University

Wireless communications may be the key solution to satisfy mobility, flexibility and scalability requirements of the Internet of Things (IoT). Particularly, the Low Power Wide Area Networks (LPWANs), operating in unlicensed bands, are promising because they permit both private and public backends. Unfortunately, their target applications are situations where sporadic transmissions are tolerated. They could not fit scenarios in which high reliability and short round trip time are required. In this paper, the LoRaWAN solution is considered for managing emergency and alarm communications. Reliability and timeliness limits have been overcome by jointly using a message replication scheme with variable payload length together with low-cost repeaters. Experiments have been carried out in both fixed and low-speed mobility scenarios (with an interfering traffic of 95 message/h generated by regular LoRaWAN co-located network). Results, in the former case, show that the success probability of confirmed messages is 100%, the 99.6% of the available data are delivered to the backend, and the average delay decreases by 150 ms. When mobility is considered (e.g., for an Automatic Guided Vehicle -AGV- use case) results confirm significant improvements for both the transaction success ratio and the data extraction rate, that significantly increase up to 95% and 87%, respectively. On the contrary, the overall average delay is not always reduced. 

LoRa (Long Range) technology, with great success in providing coverage for massive Internet-of-things (IoT) deployments, is recently being considered to complement the terrestrial networks with Low Earth Orbit (LEO) satellite connectivity. The objective is to extend coverage to remote areas for various verticals, such as logistics, asset tracking, transportation, utilities, agriculture, and maritime. However, only limited studies have realistically evaluated the effects of ground-to-satellite links due to the high cost of traditional tools and methods to emulate the radio channel. In this paper, compared to an expensive channel emulator, we propose and develop an alternative method for the experimental study of LoRa satellite links using lower-cost software defined radio (SDR). Since the working details of LoRa modulation are limited to the reverse-engineered imitations, we employ such a version on SDR platform and add easily controllable adverse channel effects to evaluate LoRa for satellite connectivity. In our work, the emulation of the Doppler effect is considered as a key aspect for testing the reliability of LoRa satellite links. Therefore, after demonstrating the correctness of the (ideal) L oRa transceiver implementation, achieving a low packet error ratio (PER) with a commercial L oRa receiver, the baseband signal is distorted to emulate the Doppler effect, mimicking a real LoRa satellite communication. The Doppler effect is related to time-on-air (ToA), bounded to communication parameters and orbit height. Higher ToAs and lower orbits decrease the link duration, mainly because of dynamic Doppler effect. 

Wireless technologies play a key role in the Industrial Internet of Things (IIoT) scenario, for the development of increasingly flexible and interconnected factory systems. A significant opportunity in this context is represented by the advent of Low Power Wide Area Network (LPWAN) wireless technologies, that enable a reliable, secure, and effective transmission of measurement data over long communication ranges and with very low power consumption. Nevertheless, reliability in harsh environments (as typically occurs in the industrial scenario) is a significant issue to deal with. Focusing on LoRaWAN, adaptive strategies can be profitably devised concerning the above tradeoff. To this aim, this paper proposes to exploit Reinforcement Learning (RL) techniques to design an adaptive LoRaWAN strategy for industrial applications. The RL is spreading in many fields since it allows the design of intelligent systems using a stochastic discrete-time system approach. The proposed technique has been implemented within a purposely designed simulator, allowing to draw a preliminary performance assessment in a real-world scenario. A high density of independent nodes per square km has been considered, showing a significant improvement (about 10%) of the overall reliability in terms of data extraction rate (DER) without compromising full compatibility with the standard specifications. © 2021 IEEE.

Currently, the applications of the Internet of Things (IoT) generate a large amount of sensor data at a very high pace, making it a challenge to collect and store the data. This scenario brings about the need for effective data compression algorithms to make the data manageable among tiny and battery-powered devices and, more importantly, shareable across the network. Additionally, considering that, very often, wireless communications (e.g., low-power wide-area networks) are adopted to connect field devices, user payload compression can also provide benefits derived from better spectrum usage, which in turn can result in advantages for high-density application scenarios. As a result of this increase in the number of connected devices, a new concept has emerged, called TinyML. It enables the use of machine learning on tiny, computationally restrained devices. This allows intelligent devices to analyze and interpret data locally and in real time. Therefore, this work presents a new data compression solution (algorithm) for the IoT that leverages the TinyML perspective. The new approach is called the Tiny Anomaly Compressor (TAC) and is based on data eccentricity. TAC does not require previously established mathematical models or any assumptions about the underlying data distribution. In order to test the effectiveness of the proposed solution and validate it, a comparative analysis was performed on two real-world datasets with two other algorithms from the literature (namely Swing Door Trending (SDT) and the Discrete Cosine Transform (DCT)). It was found that the TAC algorithm showed promising results, achieving a maximum compression rate of 98.33%. Additionally, it also surpassed the two other models regarding the compression error and peak signal-to-noise ratio in all cases. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

As the number of installed Battery Energy Storage Systems (BESSs) increases, the concerns related to possible cyberattacks to these systems rise accordingly. The most of BESS owners knows their systems may be vulnerable, but they often consider only denial of service attacks in their risk assessment. Unfortunately, other, subtler and more dangerous attacks exist. In this paper we show that a stealth attack to BESSs can be performed by applying a Man-in-the-Middle (MitM) approach. The aim of the attack is to stealthily manage the physical system by hiding the actual behavior of the system to its supervisory controller. In this case the attacker would be able to: (i) degrade the BESS by reducing its expected lifetime, (ii) produce economic losses for the prosumer, and (iii) affect the security and stability of the grid. The feasibility of the attack is demonstrated by providing an example of a stealth MitM attack on a real BESS coupled with a photovoltaic power plant. The proposed case study demonstrates that such attack can be performed without being discovered by end-users and shows that its effects can be severe. Finally, possible strategies to avoid or detect such kind of attack are discussed. IEEE

Although the idea of using wireless links for covering large areas is not new, the advent of Low Power Wide area networks (LPWANs) has recently started changing the game. Simple, robust, narrowband modulation schemes permit the implementation of low-cost radio devices offering high receiver sensitivity, thus improving the overall link budget. The several technologies belonging to the LPWAN family, including the well-known LoRaWAN solution, provide a cost-effective answer to many Internet-of-things (IoT) applications, requiring wireless communication capable of supporting large networks of many devices (e.g., smart metering). Generally, the adopted medium access control (MAC) strategy is based on pure ALOHA, which, among other things, allows to minimize the traffic overhead under constrained duty cycle limitations of the unlicensed bands. Unfortunately, ALOHA suffers from poor scalability, rapidly collapsing in dense networks. This work investigates the design of an improved LoRaWAN MAC scheme based on slotted ALOHA. In particular, the required time dissemination is provided by out-of-band communications leveraging on Radio Data System(FM-RDS) broadcasting, which natively covers wide areas both indoor and outdoor. An experimental setup based on low-cost hardware is used to characterize the obtainable synchronization performance and derive a timing error model. Consequently, improvements in success probability and energy efficiency have been validated by means of simulations in very large networks with up to 10000 nodes. It is shown that the advantage of the proposed scheme over conventional LoRaWAN communication is up to 100% when short update time and large payload are required. Similar results are obtained regarding the energy efficiency improvement, that is close to 100% for relatively short transmission intervals and long message duration; however, due to the additional overhead for listening the time dissemination messages, efficiency gain can be negative for very short duration of message fastly repeating.

The advent of the Internet of Things (IoT) paradigm highlighted the importance of core technologies at the root of any distributed systems, as wireless communications, cloud computing and big data analysis. Today, companies and organizations, pursuing the so-called Industry 4.0 (r)evolution, are moving toward smart factories, smart workforce, and intelligent transportation. The use of IoT technologies for connecting smart vehicles is identified by the IoV acronym, i.e. the Internet of Vehicle. In this work, the authors address the characterization of a distributed measurement platform for vehicle fleet management, focusing on time-related performance. In particular, a commercially available solution has been considered and real-world use cases have been identified, showing obtainable performance: with default configuration, an average overall delay less than 11 s has been estimated. © 2021 IEEE.

Low Power Wide Area Networks (LPWANs) are wireless technologies well accepted in the Internet of Things (IoT) scenarios because they operate in both public and private infrastructure using unlicensed frequency bands. Differently from other wireless standards, the LPWAN target applications are low-rate, sporadic-transmission, low-energy systems. Surely, fast response time and high reliable communication are out of the original LPWAN scope. In this work, a first investigation about the use LoRaWAN (one the most diffused LPWAN protocols) for notification of emergency messages across industrial plants is reported. The opportunity of using recently proposed low-cost repeaters, and the creation of a clever replication pattern of radio messages are the keys of the proposed approach. The results of the preliminary analytical feasibility assessment are presented, confirming the possibility to increase success ratio of notification and respective confirmation in case of emergencies. © 2021 IEEE.

The spreading of IoT in every applications triggered the creation of many IoT frameworks. Many of them are compatible with several transmission protocols to collect data from IoT end-nodes (e.g. sensors/actuators). This paper introduces a new approach for the management of multi-protocol IoT architecture with redundancy features. Assuming the functional view diagram of IoT Architecture reference project (IoT-A), adaptations in communication and management functional blocks have been introduced to support redundancy based on multi-protocol and all the related management issues. The main goal is to keep this feature transparent for the rest of the system, which includes the application and its users. An experimental setup was designed and experiments were carried out to demonstrate feasibility and to characterize performance of the proposed solution. The results show that, with the multi-protocol redundancy activated, the IoT framework is capable of transparently delivering more information to the user application. © 2021 IEEE.

In this article, industrial control systems include networked control systems (NCS), which use real-time Ethernet (RTE) protocols since many years, well before the time sensitive networking initiative debut. Today, ethernet-based control systems are used all across Industry 4.0, including in critical applications, allowing for straight integration with information technology layers. Even if it is known that current RTE protocols do not have strong authentication or ciphering options, it is still very challenging to perform undetected cyber-attacks to these protocols while the NSC is in operation, in particular because such attacks must comply with very strict and small temporal constraints. In this article, a model-based attack is proposed for service degradation of NCS. The attack is carried out in real-time and it can remain undetected for the entire plant life. The attack can be applied to any RTE protocols and, without loss of generality, a detailed analysis of stealth techniques is provided for a specific real use case based on PROFINET. The experimental results demonstrate the feasibility of the proposed attack and its high effectiveness. The article also points out some possible future investigation directions in order to mitigate the attack. © 1982-2012 IEEE.