Advanced Sensors in LoRaWAN Network
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".
Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 3288
Special Issue Editors
Interests: wireless multi-hop networks; Internet of Things; modern methods and architectures of communications; 5G-and-beyond communication
Special Issues, Collections and Topics in MDPI journals
Interests: radio access networks; game theory; performance evaluation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The ultimate goal of the Internet of Things is to provide low-cost, large-scale, and ultra-durable connectivity for every object that can benefit from being connected. LoRaWAN is a widely known IoT solution over the unlicensed band with a simplified connectivity procedure. It is designed to allow low-powered devices to communicate reliably with the access network over long-range wireless connections. However, the shortage in radio resources, random Aloha-type access and the expected massive deployment of LoRa devices lead to meagre network performances. Accordingly, savvy resource management that copes with the constrained LoRa devices is paramount to enhance the capacity of LoRaWAN. Another crucial but challenging goal is securing LoRaWAN, as it is hindered by some inherent features of LoRa devices, namely their resource-constrained nature, their diversity, and their low fault-tolerance. This special issue will shed light on two research trends in LoRaWAN: securing the error-prone access with intelligent lightweight solutions suitable with OS-constrained devices; and smart and distributed resource sharing schemes that improve packet reception while preserving ultra-long battery lifetimes of LoRa devices.The devices of a LoRaWAN network are a type of sensors. In typical applications, the devices sense various metrics (temperature, humidity, smoke, and for health wearables we have blood pressure, glucose, etc.) and send them to a central server.
Prof. Cédric Adjih
Dr. Kinda Khawam
Guest Editors
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Keywords
- LoRaWAN
- resource allocation
- machine learning
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