In an article published in the journal Nature, researchers presented a novel long-range wide area network (LoRaWAN) gateway that used edge computing to expedite the confirmed messaging process by generating local acknowledgments. This significantly reduced the confirmed messaging time, making it suitable for real-time applications like emergency alerting and controlling.
Study: Edge Computing LoRa Gateway for Real-Time Messaging. Image Credit: Ar_TH/Shutterstock
The approach also decreased network server resource utilization, reducing central processing unit (CPU), memory, and bandwidth usage while lowering the cost of the gateway by $38 compared to benchmark products.
Background
LoRaWAN has gained popularity in Internet of things (IoT) applications due to its long range and low power consumption, making it a key technology for smart cities, homes, and industrial control. LoRaWAN operates in three classes (A, B, and C) to accommodate various applications, with Class A widely used for its energy efficiency in battery-powered end nodes. However, this mode is unsuitable for real-time applications due to its limited receive windows.
Class C is more real-time, but at the cost of higher power consumption, while Class B falls in between. Despite the success of LoRaWAN, challenges arise in local deployments requiring rapid acknowledgments. The cloud-based network server can experience significant resource strain, such as high CPU, memory, and bandwidth usage, when managing confirmed packets from numerous nodes.
Additionally, confirmed messaging can take several seconds, impeding real-time operations. Previous research has explored distributed computing models and edge-computing-based architectures to optimize LoRaWAN and address these challenges. However, these studies often lack experimental validation using real-world end nodes or fail to detail hardware components and cost implications.
This paper proposed a novel edge-computing LoRaWAN gateway that reduced confirmed messaging time to milliseconds by generating local acknowledgments, thus improving real-time capabilities. Additionally, this approach decreased the network server's resource usage and overall gateway cost, offering a practical and efficient solution for real-time IoT applications.
Innovative System and Gateway Design
The system architecture integrated a mobile application, management platform, server (either local or cloud-based), LoRaWAN gateway, and end nodes to enable comprehensive monitoring and control. The mobile application and management platform allowed users to operate the end nodes and monitor their status, receiving uplink messages.
The server was central, providing data storage, processing, network services, and security. This server included a main server, a LoRaWAN server, a message queuing telemetry transport (MQTT) server, a device management server, and a database. LoRaWAN gateways were critical in this system, acting as data relays and processing hubs. The connection between the gateway and the server could be achieved through ethernet or fifth-generation (5G) networks, facilitating efficient communication.
The architecture employed a star network topology, known for its maintainability, reliability, and scalability, which connected gateways to end nodes. End nodes encompassed a variety of devices such as smart switches, motion infrared sensors, microwave radar sensors, and magnetic sensors, making the system versatile and applicable in various fields like smart homes, building automation, smart agriculture, smart cities, and environmental monitoring.
The hardware design of the gateway emphasized user-friendliness, ease of installation, and low cost. It employed a direct current (DC)-to-DC converter for power supply and the MTK7688 module for MQTT communication with the server. Regarding software design, open wireless router (OpenWRT) Linux served as the gateway's operating system, incorporating hardware drivers, middleware components, and four main processes for managing data, LoRaWAN communication, and message routing.
The gateway leveraged the MQTT protocol for efficient communication with the server. Finally, the design included considerations for efficient edge computing, such as quick response (QR) code registration for gateways, node list synchronization, and various security mechanisms that enhanced the overall performance and reliability of the system.
Findings and Performance Outcomes
The results demonstrated a significant improvement in network server and gateway performance due to the implementation of an edge-computing approach. The authors focused on reducing resource usage on the network server and enhancing gateway performance by streamlining processes at the edge. In terms of network server resource usage reduction, the experiments revealed that offloading acknowledgment generation to the edge-computing gateway drastically lowered CPU, memory, and bandwidth usage on the network server.
By handling retransmissions and security mechanisms locally at the gateway, the latency and processing overhead on the server were minimized. The approach also led to improvements in throughput and overall operational efficiency. The gateway performance was measured using eight nodes, each transmitting 100 packets to a gateway. The packet reception rate (PRR) consistently hovered around 97.38%, indicating a reliable communication path between the end nodes and the gateway.
The confirmed messaging time was also efficient, averaging around 43 milliseconds, with most messages succeeding on the first attempt. This was significantly faster than the traditional LoRaWAN Class A standard, which could take over six seconds due to multiple retransmission attempts. Overall, the proposed edge-computing approach offered substantial and consistent improvements in resource management, demonstrating the potential for more efficient and scalable IoT networks. These findings highlighted the effectiveness of local processing in reducing server workload and enhancing gateway performance, setting a new standard for IoT network optimization.
Conclusion
In conclusion, the researchers introduced an innovative edge-computing single-channel LoRaWAN gateway using MTK7688 and SX1278 modules. This gateway offered real-time confirmed messaging capabilities, addressing a gap in current gateways. It efficiently handled acknowledgments, which minimized network server resource usage. The design of the gateway is suitable for low-power, long-range IoT applications, providing cost-effective solutions where Wi-Fi fell short.
Future work will focus on integrating additional features such as user application functionalities and local command generation, enhancing the gateway's edge computing capabilities and further reducing network server resource demand.
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