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<p>LoRa communication has become a cornerstone for Internet of Things (IoT) applications due to its long-range, low-power capabilities which are ideal for remote and rural deployments such as agricultural monitoring. LoRa faces significant challenges, such as network congestion, high latency, and inefficient resource allocation that hinder its scalability and real-time data transmission capabilities. To overcome these issues, a novel enhanced LORA model using lemuR optimization for AllocatIng of SprEading factor (LORA-RAISE) approach has been proposed to enhance communication speed in LoRa. The Lemur Optimization Algorithm (LOA) is employed to optimize spreading factor allocation which improves communication performance, reduces latency, and conserves energy using parameters, such as frequency band, device power, and bandwidth to ensure robust communication. The data are processed through an Ethernet-based system, providing visual insights that facilitate informed decision-making in agriculture. The efficacy of the LORA-RAISE framework is assessed using metrics, such as delay, packet delivery ratio (PDR), throughput, and Energy Consumption (EC). The LORA-RAISE method improves communication performance and decreases latency using the LOA technique. The LORA-RAISE method achieves a throughput of 8.1%, 10.5%, and 4.6% than existing systems, such as the ADR-OWA, LORA-RSSI, and LR-RL, respectively.</p>

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Lemur Optimized Efficient Spreading Factor Allocation of LoRa Networks for IoT Deployments

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月6日

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  • J. SathiaParkavi,
  • C. Vennila

摘要

LoRa communication has become a cornerstone for Internet of Things (IoT) applications due to its long-range, low-power capabilities which are ideal for remote and rural deployments such as agricultural monitoring. LoRa faces significant challenges, such as network congestion, high latency, and inefficient resource allocation that hinder its scalability and real-time data transmission capabilities. To overcome these issues, a novel enhanced LORA model using lemuR optimization for AllocatIng of SprEading factor (LORA-RAISE) approach has been proposed to enhance communication speed in LoRa. The Lemur Optimization Algorithm (LOA) is employed to optimize spreading factor allocation which improves communication performance, reduces latency, and conserves energy using parameters, such as frequency band, device power, and bandwidth to ensure robust communication. The data are processed through an Ethernet-based system, providing visual insights that facilitate informed decision-making in agriculture. The efficacy of the LORA-RAISE framework is assessed using metrics, such as delay, packet delivery ratio (PDR), throughput, and Energy Consumption (EC). The LORA-RAISE method improves communication performance and decreases latency using the LOA technique. The LORA-RAISE method achieves a throughput of 8.1%, 10.5%, and 4.6% than existing systems, such as the ADR-OWA, LORA-RSSI, and LR-RL, respectively.