Blockchain-Enabled M2M Communications for UAV-Assisted Data Transmission

Internet of Things (IoT) technology has uncovered a wide range of possibilities in several industrial sectors where smart devices are capable of exchanging real-time data. Machine-to-machine (M2M) data exchange provides a new method for connecting and exchanging data among machine-oriented communica...

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Bibliographic Details
Published inMathematics (Basel) Vol. 11; no. 10; p. 2262
Main Authors Aldaej, Abdulaziz, Ahanger, Tariq Ahamed, Ullah, Imdad
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.05.2023
Subjects
Analysis
Automation
Blockchain
Communications networks
Communications systems
Cryptography
Data exchange
Data transmission
Decentralization
Distributed ledger
Drone aircraft
Edge computing
Electronic devices
Internet of Things
Markov processes
Mathematics
Mobile computing
Optimization
Privacy
security
unmanned aerial vehicle
Unmanned aerial vehicles
Wireless communications
Wireless networks
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Summary:Internet of Things (IoT) technology has uncovered a wide range of possibilities in several industrial sectors where smart devices are capable of exchanging real-time data. Machine-to-machine (M2M) data exchange provides a new method for connecting and exchanging data among machine-oriented communication entities (MOCE). Conspicuously, network services will be severely affected if the underneath IoT infrastructure is disrupted. Moreover, it is difficult for MOCEs to re-establish connectivity automatically. Conspicuously, in the current paper, an analysis is performed regarding potential technologies including unmanned aerial vehicles, blockchain, and mobile edge computing (MEC) that can enable the secure establishment of M2M communications networks that have been compromised to maintain the secure transmissible data. Furthermore, a Markov decision process-based joint optimization approach is proposed for blockchain systems that aims to elevate computational power and performance. Additionally, the dueling deep Q-network (DDQ) is incorporated to address the dynamic and complex optimization issue so that UAV selection is ensured to maximize performance. The results of experimental simulation with several statistical attributes suggest that the proposed framework can increase throughput optimally in comparison to state-of-the-art techniques. Additionally, a performance measure of reliability and stability depicts significant enhancement for the proposed framework.
ISSN:2227-7390
2227-7390
DOI:10.3390/math11102262