Abstract
Long-Range Wide Area Network (LoRaWAN) is an open-source protocol for the standard Internet of Things (IoT) Low Power Wide Area Network (LPWAN). This work’s focal point is the LoRa Multi-Armed Bandit decentralized decision-making solution. The contribution of this paper is to study the effect of the re-learning EXP3 Multi-Armed Bandit (MAB) algorithm with previous experts’ advice on the LoRaWAN network performance. LoRa smart node has a self-managed EXP3 algorithm for choosing and updating the transmission parameters based on its observation. The best parameter choice needs previously associated distribution advice (expert) before updating different choices for confidence. The paper proposes a new approach to study the effects of combined expert distribution for each transmission parameter on the LoRaWAN network performance. The successful transmission of the packet with optimized power consumption is the pivot of this paper. The validation of the simulation result has proven that combined expert distribution improves LoRaWAN network’s performance in terms of data throughput and power consumption.
Highlights
Nowadays, the Long-Range Wide Area Network (LoRaWAN) system can be considered a primary key of Internet of Things (IoT) services and applications
Our approach works on optimization of the Long Range (LoRa) node transmission performance by deriving transmission policies that optimize both performance and power consumption.This approach focuses on improving the performance of the IoT-LoRaWAN networks in the adversarial environment
The energy consumption per node is equal to Packet emission energy multiplied by the number of transmissions; the energy consumed for one packet is equal to the packet radiation duration multiplied by the transmission power; the number of transmissions represents the number of transmissions to send a successful packet (ACK is received)
Summary
The LoRaWAN system can be considered a primary key of IoT services and applications. LoRa physical layer technology was introduced by Semtech It has two other parameters; bandwidth (BW) can be set to 125 kHz, 250 kHz, and 500 kHz m and it uses forward error correction, adding a small overhead to the transmitted message, which provides recovery features against bit corruption. The ALOHA allows nodes to transmit as soon as they wake up and exponentially back off for saving power as much as possible and use low signaling overhead as possible. Our approach works on optimization of the LoRa node transmission performance by deriving transmission policies that optimize both performance and power consumption.This approach focuses on improving the performance of the IoT-LoRaWAN networks in the adversarial environment.
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