Blockchain and Internet of Things

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 667

Special Issue Editor

Department of Computer Science and Mathematics, Faculty of Economic Studies, University of Finance and Administration, 101 00 Prague, Czech Republic
Interests: cryptocurrency; security; XML; data compression; education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Blockchain technology and the Internet of Things (IoT) are two separate yet equally compelling innovations that are currently shaping the modern landscape. Blockchain, with its decentralized ledger and cryptographic security, has the potential to revolutionize financial transactions, supply chain management, and digital identity verification. On the other hand, the IoT, through its web of interconnected devices, offers new possibilities for data collection, automation, and real-time decision making, impacting industries like healthcare, agriculture, and smart cities. Each innovation brings unique benefits and challenges, but they share a common objective: to enhance efficiency, security, and transparency in their respective domains.

Within the scope of this Special Issue, a diverse array of advanced mathematical and statistical methods take a prominent role. These encompass a wide spectrum of techniques, including but not limited to machine learning, deep learning, algorithmic approaches, Bayesian inference, time series analysis, regression models, clustering algorithms, system theory, formal verification techniques, and rigorous modeling approaches.

This Special Issue will focus on recent theoretical and practical studies of blockchain technology and the IoT, with a focus on their independent advancements and collaborative potential, shedding light on how these innovations are shaping modern industries and influencing the future of technology. Topics include, but are not limited to, the following: 

  1. Security and Privacy;
  2. Performance and Scalability Issues;
  3. Network and Transaction Analysis;
  4. Cryptocurrency and Cryptoasset;
  5. Central Bank Digital Currency;
  6. Smart Contracts;
  7. Token Economy;
  8. Digital Identity;
  9. IoT and/or Blockchain Applications;
  10. Edge Computing in IoT;
  11. Sustainability;
  12. Healthcare;
  13. Agriculture;
  14. Smart Cities;
  15. Manufacturing and Industry;
  16. Supply Chain;
  17. Macroeconomic Studies;
  18. Social Aspects and Regulations.

Dr. Jan Lansky
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • blockchain
  • Internet of Things
  • security
  • privacy
  • performance
  • network
  • cryptocurrency
  • cryptoasset
  • distributed consensus
  • smart contracts
  • decentralized applications
  • tokens
  • digital identity
  • edge computing
  • sustainability
  • healthcare
  • agriculture
  • smart cities
  • supply chain
  • machine learning
  • deep learning
  • Bayesian inference
  • time series analysis
  • regression models
  • clustering algorithms
  • system theory
  • formal verification

Published Papers (1 paper)

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Research

26 pages, 2083 KiB  
Article
A Novel Optimized Link-State Routing Scheme with Greedy and Perimeter Forwarding Capability in Flying Ad Hoc Networks
by Omar Mutab Alsalami, Efat Yousefpoor, Mehdi Hosseinzadeh and Jan Lansky
Mathematics 2024, 12(7), 1016; https://doi.org/10.3390/math12071016 - 28 Mar 2024
Viewed by 489
Abstract
A flying ad hoc network (FANET) is formed from a swarm of drones also known as unmanned aerial vehicles (UAVs) and is currently a popular research subject because of its ability to carry out complicated missions. However, the specific features of UAVs such [...] Read more.
A flying ad hoc network (FANET) is formed from a swarm of drones also known as unmanned aerial vehicles (UAVs) and is currently a popular research subject because of its ability to carry out complicated missions. However, the specific features of UAVs such as mobility, restricted energy, and dynamic topology have led to vital challenges for making reliable communications between drones, especially when designing routing methods. In this paper, a novel optimized link-state routing scheme with a greedy and perimeter forwarding capability called OLSR+GPSR is proposed in flying ad hoc networks. In OLSR+GPSR, optimized link-state routing (OLSR) and greedy perimeter stateless routing (GPSR) are merged together. The proposed method employs a fuzzy system to regulate the broadcast period of hello messages based on two inputs, namely the velocity of UAVs and position prediction error so that high-speed UAVs have a shorter hello broadcast period than low-speed UAVs. In OLSR+GPSR, unlike OLSR, MPR nodes are determined based on several metrics, especially neighbor degree, node stability (based on velocity, direction, and distance), the occupied buffer capacity, and residual energy. In the last step, the proposed method deletes two phases in OLSR, i.e., the TC message dissemination and the calculation of all routing paths to reduce routing overhead. Finally, OLSR+GPSR is run on an NS3 simulator, and its performance is evaluated in terms of delay, packet delivery ratio, throughput, and overhead in comparison with Gangopadhyay et al., P-OLSR, and OLSR-ETX. This evaluation shows the superiority of OLSR+GPSR. Full article
(This article belongs to the Special Issue Blockchain and Internet of Things)
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