Large-scale deployment and management of Internet of Things (IoT) devices will become a critical issue in the near future. The 3rd Generation Partnership Project (3GPP) has proposed NarrowBand - Internet of Things (NB-IoT) as a new radio technology standard to enable Internet connectivity for a massive number of low-throughput devices. It supports better coverage and lower energy consumption than traditional Long-Term Evolution (LTE). The NB-IoT specification adopts the Power Saving Mode (PSM) and Extended Discontinuous Reception (eDRX) mechanisms to achieve a long battery life. In this paper, we present an energy consumption model for NB-IoT devices using PSM and eDRX, with a Poisson arrival process for uplink and downlink data transmissions. The model is compared to NS-3 simulation results. We analyze NB-IoT energy consumption for different PSM timers, eDRX timers and packet Inter-Arrival Times (IATs) based on the proposed model. Additionally, we have simulated the battery life for an NB-IoT use case on tracking shared bicycles. Comparison of the analytical model and simulation results shows consistency in the results with an average error of 11.82%. Our results also showed that with a 5 Wh battery, a device lifetime of more than 12 years can be achieved when transmitting at most one packet per day, and when properly confiauring the PSM and eDRX timers.

The Internet of Things (IoT) already connects billions of devices and keeps growing exponentially. These devices are designed to be integrated with industrial machines, home appliances and infrastructures. One such use-case is to build a smart grid management system that relies on demand-response techniques to control the appliances automatically so that the power can be distributed optimally. The mission-critical smart grid communications require secure, reliable, two-way communicable, and latency bounded connections between the management system and the electrical appliances. To realize these, cellular technology is arguably the most feasible solution. 3GPP has already released the Narrowband-Internet of Things (NB-IoT) standards as the low-power dense-area coverage IoT cellular solution. In this paper, we present an NB-IoT system to monitor and control the connected electrical appliances in a smart grid network. The platform is also capable of configuring the network dynamically. We assess the latency performance for our solution using the commercially available Orange network in Belgium. It is observed that NB-IoT enabled devices can be controlled and monitored with a maximum latency less than 8 seconds in the deep-indoor environment and within 2 seconds for the outdoor environment.

Tiny batteryless Internet of Things (IoT) devices that depend on the harvested energy from their environment provide a promising alternative for a sustainable IoT vision. These devices use small capacitors as energy storage, which together with the unpredictable and dynamic harvesting environment results in intermittent on–off behavior of the device. The crucial issue to effectively use batteryless IoT devices is to find a way of enabling the successful execution of application tasks in face of this intermittency. As the conventional computing models cannot handle this behavior, in this article, we present an energy-aware task scheduler for batteryless IoT devices based on dependencies and priorities, which can intelligently schedule the application tasks avoiding power failures and maintaining forward progress. With the properly defined voltage thresholds for each application task, using our energy-aware task scheduler a safer execution can be ensured. We evaluate our approach based on emulated and real experiments and validate it using two types of power management units (PMUs) (environment emulator and intelligent PMU based on the AEM10941 chip). Our results show that the energy-aware task scheduler is able to react and adapt the execution to environmental changes, avoiding power failures. Comparing to the state-of-the-art scheduling approaches, which are mostly not aware of the energy, we show that our energy-aware task scheduler can keep the device on during the full time of the experiment, executing more tasks when a relatively small capacitor of 10 mF or less is used at harvesting currents as low as $40 ~\mu \text{A}$ .

Narrowband Internet of Things (NB-IoT) is becoming one of the most promising low-power wide area (LPWA) networking technologies. It can support more than 50 000 devices within a cell using licensed spectrum. NB-IoT provides low energy consumption, reliable connectivity and deep indoor coverage for the device, making it a good candidate for IoT use cases. NB-IoT introduces two novel energy-saving techniques, namely, extended discontinuous reception (eDRX) and power saving mode (PSM). This article presents a Markov chain model to evaluate the power consumption and latency of NB-IoT devices using PSM and eDRX. By exploiting the characteristics of the steady-state distribution of the Markov chain, the probabilities in steady-state can be obtained explicitly. Based on these probabilities, we calculate the system downlink (DL) latency as a function of different timers of these power-saving features. We also compare the model to simulation results obtained from the ns-3 event-based network simulator, to determine its accuracy. The results show that its performance in terms of energy and latency is comparable. Our model is accurate with consideration of the protocol details and the new radio resource control (RRC) Idle features of NB-IoT. The results show that the analytical model achieves an average accuracy of more than 91% for power consumption and DL latency. Lastly, we use the model to automatically determine the optimal parameter set in terms of latency and power consumption for various IoT use cases with different traffic requirements, based on multiobjective analysis of the Pareto front.

With the emerging deployment of Internet of Things devices, the industry is moving toward batteryless, maintenance-free, and sustainable solutions. Energy harvesting from ambient sources becomes crucial to support the uninterrupted execution of such applications. We choose the Bluetooth Low Energy (BLE) mesh network to analyze a batteryless node using the BLE Low power node (LPN) feature. We develop a prototype using a mini photovoltaic solar panel for indoor light harvesting using sunlight or a light bulb to power the BLE LPN. Due to the unpredictability of energy harvesting and the use of a small capacitor instead of a battery, the BLE LPN’s power can become intermittent. This causes the device to frequently switch between the ON and OFF states as it is unaware of its available energy while trying to perform scheduled tasks. In contrast, an energy-aware LPN can try to avoid the OFF state. With the knowledge of the capacitor voltage, it can proactively delay the execution of upcoming sensing or communication tasks and provide some time to recharge the capacitor while consuming a minimum amount of energy by switching itself to the SLEEP state. This article presents the developed prototype and evaluates an energy-unaware and -aware batteryless BLE LPN communicating uni-directional downlink only or bi-directional for different capacitor sizes at different light-harvesting powers. The experimental results conclude that the energy-aware batteryless LPN performs better for both uni- and bi-directional communication with improved DL data latency up to 74% and avoiding restarts.