Network Partitioning Problem and UAVs' Integration for Efficient Connectivity Restoration: A Systematic Review DOI Open Access
Aditi Zear, Virender Ranga, Kriti Bhushan

и другие.

International Journal of Communication Systems, Год журнала: 2024, Номер 38(3)

Опубликована: Дек. 30, 2024

ABSTRACT Wireless sensor and actor networks (WSANs) are gaining substantial recognition because of their utility in inhospitable environments where humans have restricted accessibility. The extensive applications WSANs different domains require effectiveness, reliability, some degree robustness. These may experience frequent node failures due to deployment rough environments, such as energy depletion onboard electronics failure network nodes. result areas with no coverage, which further deteriorate the standard data accumulated. However, partitioning into disjoint fragments is most severe repercussion that arises these failures. results various negative impacts like obstruction exchange coordination among Therefore, detecting restoring connectivity important. This paper reviews reported partition detection recovery techniques. limitations techniques highlighted, along advantages incorporating unmanned aerial vehicles (UAVs) ground wireless networks. UAVs evolving become a critical element future technologies. incorporates analysis UAV‐assisted consisting technical issues, challenges, requirements related UAVs' employment Thereafter, discussed application scenarios for problem. also highlights challenges associating process.

Язык: Английский

Human Machine Teaming in Mobile Miniaturized Aviation Logistics Systems in Safety-Critical Settings DOI Creative Commons

Ginny Morgan,

Martha Grabowski

Journal of Safety and Sustainability, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

A cross-layer PUF-secured energy and congestion-aware on-demand routing for multi-UAV networks DOI
Indu Chandran, Kizheppatt Vipin

Computer Networks, Год журнала: 2025, Номер unknown, С. 111076 - 111076

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Maximizing the Energy Efficiency using M-PSO in Multi-Hop UAV-IRS Network for Improved Post-Disaster Emergency Communication Services DOI
Humairah Hamid, Gh. Rasool Begh

Vehicular Communications, Год журнала: 2025, Номер unknown, С. 100920 - 100920

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Integrated GNSS reflectometry and UAV sensing for flood monitoring and risk mitigation DOI

Vignesh Paranjothi Vanaja,

Muhammad Hussain,

C. Siva

и другие.

AIP conference proceedings, Год журнала: 2025, Номер 3259, С. 060001 - 060001

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

EGBCR-FANET: Enhanced Genghis Khan Shark Optimizer based Bayesian-Driven Clustered Routing Model for FANETs DOI
Reham R. Mostafa,

Dilna Vijayan,

Ahmed M. Khedr

и другие.

Vehicular Communications, Год журнала: 2025, Номер unknown, С. 100935 - 100935

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Real‐Time Anomaly Detection in Smart Vehicle‐To‐UAV Networks for Disaster Management DOI
Tanveer Ahmad, Muhammad Usman Hadi, Vasos Vassiliou

и другие.

Transactions on Emerging Telecommunications Technologies, Год журнала: 2025, Номер 36(5)

Опубликована: Май 1, 2025

ABSTRACT In disaster situations, conventional vehicular communication networks often face heavy congestion, which hinders the effectiveness of Vehicle‐to‐Vehicle (V2V) communication. To overcome this issue, Vehicle‐to‐Unmanned Aerial Vehicle (V2U) is a crucial alternative, offering an expanded network infrastructure for real‐time information sharing. Nonetheless, both V2V and V2U are vulnerable to cyber‐physical disruptions caused by malicious attacks, signal interference, environmental factors. This paper introduces advanced anomaly detection framework tailored disaster‐response networks, combines discrete‐time Markov chain (DTMC) with machine learning (ML) methods. The model employs DTMC define normal transmission behavior while adaptively modifying state transition probabilities through ML techniques using data. simulations in MATLAB validate proposed method analyzing log‐likelihood maneuver patterns evaluating performance Receiver Operating Characteristic (ROC) curves. Our findings reveal that hybrid DTMC‐ML successfully detects anomalies achieving high true positive rate reducing false alarms. research aids advancing resilient systems response, thereby improving reliability security intelligent transportation extreme situations.

Язык: Английский

Процитировано

0

Proposal of a method to observe road status using UAV considering post-disaster urgency based on mobile spatial dynamics data DOI Creative Commons
Jun Sakamoto

Discover Sustainability, Год журнала: 2025, Номер 6(1)

Опубликована: Май 26, 2025

Язык: Английский

Процитировано

0

From 6G to SeaX-G: Integrated 6G TN/NTN for AI-Assisted Maritime Communications—Architecture, Enablers, and Optimization Problems DOI Creative Commons
Anastasios Giannopoulos, Panagiotis K. Gkonis, Alexandros Kalafatelis

и другие.

Journal of Marine Science and Engineering, Год журнала: 2025, Номер 13(6), С. 1103 - 1103

Опубликована: Май 30, 2025

The rapid evolution of wireless communications has introduced new possibilities for the digital transformation maritime operations. As 5G begins to take shape in selected nearshore and port environments, forthcoming 6G promises unlock transformative capabilities across entire domain, integrating Terrestrial/Non-Terrestrial Networks (TN/NTN) form a space-air-ground-sea-underwater system. This paper presents comprehensive review how 6G-enabling technologies can be adapted address unique challenges Maritime Communication (MCNs). We begin by outlining reference architecture heterogeneous MCNs reviewing limitations existing deployments at sea. then explore key technical advancements map them use cases such as fleet coordination, just-in-time logistics, low-latency emergency response. Furthermore, critical Artificial Intelligence/Machine Learning (AI/ML) concepts algorithms are described highlight their potential optimizing functionalities. Finally, we propose set resource optimization scenarios, including dynamic spectrum allocation, energy-efficient edge offloading MCNs, discuss AI/ML learning-based methods offer scalable, adaptive solutions. By bridging gap between emerging practical requirements, this highlights role intelligent, resilient, globally connected networks shaping future communications.

Язык: Английский

Процитировано

0

UGV-UAV Integration Advancements for Coordinated Missions: A Review DOI Creative Commons
Farah Syazwani Shahar, Mohamed Thariq Hameed Sultan, Marek Nowakowski

и другие.

Journal of Intelligent & Robotic Systems, Год журнала: 2025, Номер 111(2)

Опубликована: Июнь 2, 2025

Язык: Английский

Процитировано

0

Comparative Reliability Analysis of Unmanned Aerial Vehicle Swarm Based on Mathematical Models of Binary-State and Multi-State Systems DOI Open Access
Elena Zaitseva, Ravil I. Mukhamediev, Vitaly Levashenko

и другие.

Electronics, Год журнала: 2024, Номер 13(22), С. 4509 - 4509

Опубликована: Ноя. 17, 2024

A key aspect in evaluating the performance of a UAV or its swarm is reliability. The reliability calculated based on various mathematical models. Traditionally, Binary-State System (BSS) models, which assess two states—operational and faulty—are employed. However, some studies suggest using Multi-State (MSS) model, allows for detailed analysis by considering multiple states beyond just operational faulty. Both models allow evaluation Unmanned Aerial Vehicle (UAV) swarms availability, considered as probability mission implementation. There one more similar assessment computed MSS, named probabilities level. are not any recommendations applications these assessments analyses swarms. This paper introduces comparative study availability both BSS MSS levels provides quantitative qualitative to exploit according computational complexity informativeness. shows that failure should be BSS, operation implemented probabilities’ instead availability. These results confirmed statistical examinations different types MSS. number UAVs changed from 2 20 examinations.

Язык: Английский

Процитировано

1