Adaptive Parameters for LoRa-Based Networks Physical-Layer.

Sub-GHz communication provides long-range coverage with low power consumption and reduced deployment cost. LoRa (Long-Range) has emerged, among existing LPWAN (Low Power Wide Area Networks) technologies, as a promising physical layer alternative to provide ubiquitous connectivity to outdoor IoT devices. LoRa modulation technology supports adapting transmissions based on parameters such as carrier frequency, channel bandwidth, spreading factor, and code rate. In this paper, we propose SlidingChange, a novel cognitive mechanism to support the dynamic analysis and adjustment of LoRa network performance parameters. The proposed mechanism uses a sliding window to smooth out short-term variations and reduce unnecessary network re-configurations. To validate our proposal, we conducted an experimental study to evaluate the performance concerning the Signal-to-Noise Ratio (SNR) parameter of our SlidingChange against InstantChange, an intuitive mechanism that considers immediate performance measurements (parameters) for re-configuring the network. The SlidingChange is compared with LR-ADR too, a state-of-the-art-related technique based on simple linear regression. The experimental results obtained from a testbed scenario demonstrated that the InstanChange mechanism improved the SNR by 4.6%. When using the SlidingChange mechanism, the SNR was around 37%, while the network reconfiguration rate was reduced by approximately 16%.

Energy Consumption Evaluation of a Routing Protocol for Low-Power and Lossy Networks in Mesh Scenarios for Precision Agriculture.

Sensor nodes are small, low-cost electronic devices that can self-organize into low-power networks and are susceptible to data packet loss, having computational and energy limitations. These devices expand the possibilities in many areas, like agriculture and urban spaces. In this work, we consider an IoT environment for monitoring a coffee plantation in precision agriculture. We investigate the energy consumption under low-power and lossy networks considering three different network topologies and an Internet Engineering Task Force (IETF) standardized Low-power and Lossy Network (LLN) routing protocol, the Routing Protocol for LLNs (RPL). For RPL, each secondary node selects a better parent according to some Objective Functions (OFs). We conducted simulations using Contiki Cooja 3.0, where we considered the Expected Transmission Count (ETX) and hop-count metric (HOP) metrics to evaluate energy consumption for three distinct topologies: tree, circular, and grid. The simulation results show that the circular topology had the best (lowest) energy consumption, being 15% better than the grid topology and 30% against the tree topology. The results help the need to improve the evolution of RPL metrics and motivate the network management of the topology.