Billions of IoT devices are deployed worldwide and batteries are their main power source. However, these batteries are bulky, short-lived and full of hazardous chemicals that damage our environment. Relying on batteries is not a sustainable solution for the future IoT. As an alternative, battery-less devices run on long-lived capacitors charged using energy harvesters. The small energy storage capacity of capacitors results in an intermittent on-off behaviour. LoRaWAN is a popular Low Power Wide Area Network technology used in many IoT devices and can be used in these new scenarios. In this work, we present a Markov model to characterize the performance of battery-less LoRaWAN devices for uplink and downlink transmissions and we evaluate their performance in terms of the parameters that define the model (i.e., device configuration, application behaviour and environmental conditions). Results show that LoRaWAN battery-less communications are feasible if choosing the proper configuration (i.e., capacitor size, turn-on voltage threshold) for different application behaviour (i.e., transmission interval, UL/DL packet sizes) and environmental conditions (i.e., energy harvesting rate). Since downlink in the second reception window highly affects the performance, only small DL packet sizes should be considered for these devices. Besides, a 47 mF capacitor can support 1 Byte SF7 transmissions every 60 s at an energy harvesting rate of 1 mW. However, if no DL is expected, a 4.7 mF capacitor could support 1 Byte SF7 transmissions every 9 s.

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.

Deploying low maintenance and long-life systems is an important requirement of emerging commercial Internet of Things (IoT) solutions. Such systems can be envisioned in which the connected devices are powered by energy harvested from ambient sources and stored in long-lifetime capacitors rather than short-lived and polluting batteries. However, due to the unpredictable nature of ambient energy harvesting, such batteryless IoT devices might not always have enough energy to initiate communication. The Bluetooth Low Energy (BLE) specification defines support for Low Power Nodes (LPNs) using the friendship feature, where the LPN is associated with a neighbouring friend node (FN). The LPN can receive downlink (DL) data and remain connected to the network via the FN that buffers the LPN’s incoming packets while allowing the LPN to save energy by sleeping or turning itself off. This novel BLE feature makes the LPN highly suitable to support the connection of batteryless ambiently-powered IoT devices. While the LPN can decide when to transmit uplink (UL) packets and does not depend on the FN to receive downlink (DL) data, the LPN needs to poll its FN to receive the buffered packets. However, the DL packet latency increases with this process due to the buffering time at the FN. Therefore, in this work, we present an analytical model to characterize the performance as a function of DL data latency and packet delivery ratio (PDR) of a batteryless LPN powered by different harvesting powers and capacitor sizes. This would help to optimally choose the correct configuration of the batteryless LPN for its network deployment. We also compare the analytical model and simulation results, showing consistency with an average error of 2.23% for DL data latency and 0.09% for the PDR.

In a world with a growing elderly population, Wireless Body Area Networks (WBANs) are considered an opportunity to supply healthcare to a growing number of patients requiring continuous medical care. A large number of WBAN sensors, radios, medium access and routing protocols has already been developed and is actively being developed. Together with an increasing number of applications and field trials, this illustrates how promising WBANs are, both to academia and industry. Currently, WBANs are almost always assumed to have a single-hop topology, where all nodes on the body are in range of the central sink device. However, to conserve energy and to limit exposure of the human body to radiation, research indicates the need to support multi-hop topologies. In those small-scale topologies, a small body movement can cause a complete topology reorganization or more general node mobility. This work analyzes three algorithm variants to support these mobile WBANs, with respect to channel utilization and energy efficiency, in both a static and a mobile scenario.