# Research and Design of a Decentralized Edge-Computing-Assisted LoRa Gateway
###### Abstract  
As a narrowband communication technology, long-range (LoRa) contributes to the long development of Internet of Things (IoT) applications. The LoRa gateway plays an important role in the IoT transport layer, and security and efficiency are the key issues of the current research. In the centralized working model of IoT systems built by traditional LoRa gateways, all the data generated and reported by end devices are processed and stored in cloud servers, which are susceptible to security issues such as data loss and data falsification. Edge computing (EC), as an innovative approach that brings data processing and storage closer to the endpoints, can create a decentralized security infrastructure for LoRa gateway systems, resulting in an EC-assisted IoT working model. Although this paradigm delivers unique features and an improved quality of service (QoS), installing IoT applications at LoRa gateways with limited computing and memory capabilities presents considerable obstacles. This article proposes the design and implementation of an \"EC-assisted LoRa gateway\" using edge computing. Our proposed latency-aware algorithm (LAA) can greatly improve the reliability of the network system by using a distributed edge computing network technology that can achieve maintenance operations, such as detection, repair, and replacement of failures of edge nodes in the network. Then, an EC-assisted LoRa gateway prototype was developed on an embedded hardware system. Finally, experiments were conducted to evaluate the performance of the proposed EC-assisted LoRa gateway. Compared with the conventional LoRa gateway, the proposed edge intelligent LoRa gateway had 41.1% lower bandwidth utilization and handled more end devices, ensuring system availability and IoT network reliability more effectively. LoRa gateway; edge computing network; internet of things; embedded system; distributed computing +
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With the development of IoT and communication technology, more and more sensor devices are connected to the IoT in various ways, and a large amount of data is generated as a result. This massive amount of data causes several issues, including excessive latency, necessitating a larger bandwidth. Transmission of data between cloud centers and IoT devices will result in significant delays. Edge computing may deliver services at the network's edge to minimize latency and provide edge data processing power and security [2]. Edge computing became popular as a result of the installation of servers at the edge [3]. Edge computing employs a decentralized strategy that allows application processing and task execution to occur locally. In this manner, the network traffic issue is reduced. In edge computing, access to resources is provided at the network's edge [4], close to end devices, which has a significant influence on bandwidth and minimizes communication latency [5]. With the development of edge computing technology, the processing power of traditional cloud computing can be partially migrated to the LoRa gateway. This decentralized strategy may aid in preventing the falsification of data when applied to the LoRa gateway. Consequently, an EC-assisted LoRa gateway is anticipated to enhance both computing performance and security. The issue of job scheduling in the LoRa gateway using edge computing is an essential subject of debate. A lot of research has focused on the job scheduling of edge computing resources in recent years. Nonetheless, the majority of past initiatives have encountered two significant limitations, namely a lack of practicability and a lack of generalizability. Existing simulation-based systems, for instance, are inapplicable to the majority of real-world circumstances. Most present solutions are appropriate for a limited range of IoT applications but cannot be generalized to compute-intensive and time-sensitive applications.