{"title":"Energy-efficient multi-hop LoRa broadcasting with reinforcement learning for IoT networks","authors":"Xueshuo Chen, Yuxing Mao, Yihang Xu, Wenchao Yang, Chunxu Chen, Bozheng Lei","doi":"10.1016/j.adhoc.2024.103729","DOIUrl":null,"url":null,"abstract":"<div><div>Low power wide area networks (LPWAN) have grown significantly in popularity recently, and long-range (LoRa) technologies have drawn notice as a branch of LPWAN. Nevertheless, most current research primarily concentrates on optimizing communication protocols or mechanisms for the LoRa uplink. Considering the demand for large-scale data distribution in the IoT environment, we propose a novel mechanism for LoRa broadcasting with formula derivation and parameter analysis. This scheme adopts the advantages of both LoRa protocols and multi-hop technology that make the data quickly spread to all devices from the center of an area.This scheme optimizes transmission energy consumption by selecting proper relays to alleviate the problem of power shortage in LoRa devices. In this paper, we design an algorithm based on machine learning and reinforcement learning to reduce transmission costs for LoRa devices. The superiority of the proposed scheme in saving communication resources has been demonstrated compared to traditional methods. When broadcasting data downstream, it can save approximately 87.4% of the time. Moreover, through simulation analysis, the proposed algorithm can save at least 12.61% transmitting energy under constraints comparing with the benchmark algorithms.</div></div>","PeriodicalId":55555,"journal":{"name":"Ad Hoc Networks","volume":"169 ","pages":"Article 103729"},"PeriodicalIF":4.4000,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ad Hoc Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1570870524003408","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Low power wide area networks (LPWAN) have grown significantly in popularity recently, and long-range (LoRa) technologies have drawn notice as a branch of LPWAN. Nevertheless, most current research primarily concentrates on optimizing communication protocols or mechanisms for the LoRa uplink. Considering the demand for large-scale data distribution in the IoT environment, we propose a novel mechanism for LoRa broadcasting with formula derivation and parameter analysis. This scheme adopts the advantages of both LoRa protocols and multi-hop technology that make the data quickly spread to all devices from the center of an area.This scheme optimizes transmission energy consumption by selecting proper relays to alleviate the problem of power shortage in LoRa devices. In this paper, we design an algorithm based on machine learning and reinforcement learning to reduce transmission costs for LoRa devices. The superiority of the proposed scheme in saving communication resources has been demonstrated compared to traditional methods. When broadcasting data downstream, it can save approximately 87.4% of the time. Moreover, through simulation analysis, the proposed algorithm can save at least 12.61% transmitting energy under constraints comparing with the benchmark algorithms.
期刊介绍:
The Ad Hoc Networks is an international and archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in ad hoc and sensor networking areas. The Ad Hoc Networks considers original, high quality and unpublished contributions addressing all aspects of ad hoc and sensor networks. Specific areas of interest include, but are not limited to:
Mobile and Wireless Ad Hoc Networks
Sensor Networks
Wireless Local and Personal Area Networks
Home Networks
Ad Hoc Networks of Autonomous Intelligent Systems
Novel Architectures for Ad Hoc and Sensor Networks
Self-organizing Network Architectures and Protocols
Transport Layer Protocols
Routing protocols (unicast, multicast, geocast, etc.)
Media Access Control Techniques
Error Control Schemes
Power-Aware, Low-Power and Energy-Efficient Designs
Synchronization and Scheduling Issues
Mobility Management
Mobility-Tolerant Communication Protocols
Location Tracking and Location-based Services
Resource and Information Management
Security and Fault-Tolerance Issues
Hardware and Software Platforms, Systems, and Testbeds
Experimental and Prototype Results
Quality-of-Service Issues
Cross-Layer Interactions
Scalability Issues
Performance Analysis and Simulation of Protocols.