Standard protocols for wireless Internet of Things (IoT) communication must be energy-efficient in order to prolong the lifetimes of IoT devices. Two energy-saving strategies for wireless communication are prevalent within the IoT domain: 1) sleepy devices and 2) radio duty cycling. In this paper, we conduct a comprehensive evaluation as to what types of application scenarios benefit the most from either type of energy-saving strategy. We select the lightweight machine to machine (LwM2M) protocol for this purpose because it operates atop the standard constrained application protocol, and has support for sleepy devices through its Queue Mode. We implement the Queue Mode at both the server side and client side, and design enhancements of Queue Mode to further improve the performance. In our experimental evaluation, we compare the performance and characteristics of Queue Mode with that of running LwM2M in a network stack with the standard time-slotted channel hopping as the duty cycling medium access control protocol. By analyzing the results with the support of an empirical model, we find that each energy-saving strategy has different advantages and disadvantages depending on the scenario and traffic pattern. Hence, we also produce guidelines that can help developers to select the appropriate energy-saving strategy based on the application scenario.

The Internet of Things (IoT) is projected to soon interconnect tens of billions of new devices, in large part also connected to the Internet. IoT devices include both high-end devices which can use traditional go-to operating systems (OSs) such as Linux, and low-end devices which cannot, due to stringent resource constraints, e.g., very limited memory, computational power, and power supply. However, large-scale IoT software development, deployment, and maintenance requires an appropriate OS to build upon. In this paper, we thus analyze in detail the specific requirements that an OS should satisfy to run on low-end IoT devices, and we survey applicable OSs, focusing on candidates that could become an equivalent of Linux for such devices, i.e., a one-size-fits-most, open source OS for low-end IoT devices.

Energy efficient sensing is one of the main objectives in the design of networked embedded monitoring systems. However, existing approaches such as duty cycling and ambient energy harvesting face challenges in railway bridge health monitoring applications due to the unpredictability of train passages and insufficient ambient energy around bridges. This paper presents ECOVIBE (Eco-friendly Vibration), an on-demand sensing system that automatically turns on itself when a train passes on the bridge and adaptively powers itself off after finishing all tasks. After that, it goes into an inactive state with near-zero power dissipation. ECOVIBE achieves these by: Firstly, a novel, fully passive event detection circuit to continuously detect passing trains without consuming any energy. Secondly, combining train-induced vibration energy harvesting with a transistor-based load switch, a tiny amount of energy is sufficient to keep ECOVIBE active for a long time. Thirdly, a passive adaptive off control circuit is introduced to quickly switch off ECOVIBE. Also this circuit does not consume any energy during inactivity periods. We present the prototype implementation of the proposed system using commercially available components and evaluate its performance in real-world scenarios. Our results show that ECOVIBE is effective in railway bridge health monitoring applications.

For telemedicine, Wireless Body Area Network (WBAN) offers enormous benefits where a patient can be remotely monitored without compromising the mobility of remote treatments. With the advent of high capacity and reliable wireless networks, WBANs are used in several remote monitoring systems, limiting the COVID-19 spread. The sensitivity of telemedicine applications mandates confidentiality and privacy requirements. In this paper, we propose a secure WBAN-19 telemedicine system to overcome the pervasiveness of contagious deceases utilizing a novel aggregate identity-based signcryption scheme with an equality test feature. We demonstrate a security analysis regarding indistinguishable adaptive chosen-ciphertext attack (IND-CCA2), one-way security against adaptive chosen-ciphertext attack (OW-CCA2), and unforgeability against adaptive chosen-message attack (EUF-CMA) under the random oracle model. The security analysis of the scheme is followed by complexity evaluations where the computation cost and communication overhead are measured. The evaluation demonstrates that the proposed model is efficient and applicable in telemedicine systems with high-performance capacities. 

There is unanimous consensus that cyber security in the IoT is necessary. In cyber security, key establishment is one of the toughest problems. It is even more challenging in resource-constrained but Internet-connected IoT devices that use low-power wireless communication. A number of IoT communication protocols define cryptographic mechanisms for confidentiality and integrity services but do not specify key management. For example, IEEE 802.15.4, RPL, and object security all rely on external key management protocols. Due to the lack of automatic key management support, IoT devices either end up using pre-shared keys or no security at all. In this paper we overcome these challenges and present TinyIKE, a lightweight adaptation of IKEv2 for the IoT. Using TinyIKE, we solve the key establishment problem for multiple IoT protocols using a single IKEv2-based solution. We implement TinyIKE for resource-constrained IoT devices that run the Contiki OS. The TinyIKE implementation supports full certificate-based IKEv2 that uses Elliptic Curve Cryptography (ECC). In order to ensure the feasibility of TinyIKE in the IoT, we perform an extensive evaluation of TinyIKE using a setup consisting of real IoT hardware.

A 5G network’s use-case in the Internet of Things (IoT) is a breakthrough, offering networks the ability to handle billions of connected devices with the proper blend of speed, latency, and cost. The IoT networks implemented in highspeed scenarios like intra and inter-vehicular communications in autonomous driving vehicles, high-speed vehicles, and trains will experience a Doppler effect. Orthogonal frequency-division multiplexing, popular transmission technology for existing newradio IoT (NR-IoT), is limited in providing reliable connections in high-speed vehicular scenarios. The performance of such system degrades with higher-order antenna configuration due to the lack of channel state information in highly mobile environments. The recently proposed orthogonal time-frequency space (OTFS) modulation is a strong contender that can handle high mobility but requires efficient transceiver design to be deployed in vehicular NR-IoT (V-IoT) systems. To conserve the resources and minimize the air time of the devices, we have proposed an embedded pilot design in the Delay-Doppler domain for the V-IoT systems. In the designed frame structure, the pilot’s position is optimized as per the vehicle speed to maximize the spectral efficiency of the system. The increase in spectral efficiency is at the cost of interference in the channel search region of the received Delay-Doppler domain OTFS signal. So a new joint estimator and low-complex detector is proposed to handle the interference. The proposed efficient transceiver design with the spectral efficient pilot patterns allow us to conserve resources and remove complex encoder-decoders like the low-density parity check in NR-IoT.