Optimal Configuration of LoRa Networks in Smart Cities

Abstract

Long Range (LoRa) is a wireless communication standard specifically targeted for resource-constrained Internet of Things (IoT) devices. LoRa is a promising solution for smart city applications as it can provide long-range connectivity with a low energy consumption. The number of LoRa-based networks is growing due to its operation in the unlicensed radio bands and the ease of network deployments. However, the scalability of such networks suffers as the number of deployed devices increases. In particular, the network performance drops due to increased contention and interference in the unlicensed LoRa radio bands. This results in an increased number of dropped messages and, therefore, unreliable network communications. Nevertheless, network performance can be improved by appropriately configuring the radio parameters of each node. To this end, we formulate integer linear programming models to configure LoRa nodes with the optimal parameters that allow all devices to reliably send data with a low energy consumption. We evaluate the performance of our solutions through extensive network simulations considering different types of realistic deployments. We find that our solution consistently achieves a higher delivery ratio (up to 8% higher) than the state of the art with minimal energy consumption. Moreover, the higher delivery ratio is achieved by a large percentage of nodes in each network, thereby resulting in a fair allocation of radio resources. Finally, the optimal network configurations are obtained within a short time, usually much faster than the state of the art. Thus, our solution can be readily used by network operators to determine optimal configurations for their IoT deployments, resulting in improved network reliability.

A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

“…In this paper, we performed a comprehensive analysis of solutions that have been developed to optimize ADR algorithms. The proposed optimization techniques address specific challenges such as scalability [ 28 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ], throughput [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ] and energy efficiency [ 20 , 46 , 47 , 48 , 49 , 50 , 51 ]. Our analysis distinguished the approaches used and highlighted the challenges and performance in the studies considered.…”

“…The challenge of conserving energy in LoRaWAN networks is a QoS in the ADR algorithms in [ 20 , 46 , 47 , 48 , 49 , 50 , 51 ]. In [ 20 ] they first optimize every end node to minimise the ToA, which is determined by its distance from the gateway, searching for optimal gateway location ensuring all nodes are connected.…”

“…Although the results show that optimisation can yield higher PDR and lower energy consumption, interference from other ISM frequency users was not considered in this approach, yet it could be a crucial factor which affects the performance. In [ 46 ] they also optimise two parameters, first they optimise SF allocation to ensure reliable communication and then optimise TP to minimise energy consumption in the network. The approach guarantees that a significant proportion of end nodes communicates reliably with a high PDR.…”

“…In [ 46 ] the authors aim to optimally transmit data with a high PDR whilst maintaining a low energy utilization. They introduce integer linear programming models to establish the optimum allocation of the parameters by considering the distribution of the end nodes and the impact of transmissions from the surrounding end nodes.…”

Red de monitorización para automatizar el sistema de enfriamiento de un centro de datos

“…Las investigaciones recientes del uso de la tecnología LoRa, donde se requiere largo alcance, han tenido como resultado avances importantes en diferentes ámbitos de la vida humana y monitorización de procesos. Se han realizado, por ejemplo, aplicaciones de esta tecnología en ciudades [18], hogares [19] y edificios inteligentes [20], granjas y campos de cultivo [21], cuidado de la salud [22] y hospitales, procesos industriales [23], consumo de energía eléctrica [24] y agua [25], control de sistemas de calefacción [26], seguridad [27], fluidos [28] y localización [29], entre otras.…”