QoS Based IoT Applications in LoRa Networks Using Multi-Dimensional Allocation Strategy

Abstract

LoRaWAN (Long Range Wide Area Network) technology has emerged as a leading solution for wireless communication in the Internet of Things (IoT) domain. With forecasts suggesting an unprecedented 500 billion IoT devices interconnected by 2030, the demand for efficient IoT applications has never been greater. LoRa technology offers low-power, long-range data transmission, addressing key requirements of IoT applications such as smart cities, agriculture, and industrial automation. This paper explores the challenges and advancements in LoRaWAN networks, focusing on Quality of Service (QoS) requirements. While traditional research efforts have primarily addressed network performance and energy optimization, the heterogeneous nature of IoT applications presents new challenges. The absence of QoS guarantees in legacy LoRaWAN protocols necessitates novel approaches to address diverse application needs. Moreover, the reliance of LoRaWAN on the Aloha access scheme introduces fundamental constraints for QoS consideration, making it difficult to develop complex algorithms for traffic control. Through a comprehensive review of existing algorithms, this paper evaluates strategies for managing QoS in heterogeneous LoRaWAN networks. By synthesizing the strengths of multiple algorithms, our proposed approaches, MixRA-opt and MixRA-H, aim to optimize network capacity and ensure satisfactory service levels for all applications, especially for large-scale, heavy-load scenarios. MixRA-opt is an optimization approach, while MixRA-H is a heuristic approach that serves as a simple approximation of the optimized method. The study includes simulations to validate the effectiveness of the proposed algorithms and provides insights for future research directions.

Keywords

• Data extraction rate
• Internet of Things
• LoRa
• LoRaSim
• optimization
• packet delivery ratio