End-to-End Delay Analysis in Aerial-Terrestrial Heterogeneous Networks

Chen, Yu-Jia; Liao, Kai-Min; Chen, Yung‐Fang

doi:10.1109/tvt.2021.3052250

Cited by 11 publications

(5 citation statements)

References 40 publications

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“…Moreover, the authors used the stochastic model to guarantee the robustness of transmission delay performance in heterogeneous networks. 105 It is concluded that trajectory can plan important role in delay performance compared to the number of UAVs. A more dynamic network could be considered in which the ground devices can be served by either ground BS or aerial BS.…”

Section: Delay Minimizationmentioning

confidence: 97%

“…Mobility of ground users could also be considered to enhance the scope of proposed work. Moreover, the authors used the stochastic model to guarantee the robustness of transmission delay performance in heterogeneous networks 105 . It is concluded that trajectory can plan important role in delay performance compared to the number of UAVs.…”

Section: Research On Enhancing Qos and Delay Minimization In Uav‐assi...mentioning

confidence: 99%

See 1 more Smart Citation

Resource optimization in UAV‐assisted wireless networks—A comprehensive survey

Basharat

Naeem

Qadir

et al. 2022

Trans Emerging Tel Tech

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Unmanned aerial vehicles (UAVs) are inevitable to meet the requirements of future wireless networks. Recently, researchers have investigated diverse issues related to UAV‐assisted networks (including placement of UAVs, resource management, and spectrum sharing) for a broad range of applications, including disaster management, data collection from the ground sensor network, surveillance, logistic support, etc. This article presents a comprehensive survey of recent advances in UAV‐assisted networks. We mainly emphasize the optimization perspective of UAV‐assisted wireless networks with different objectives, including coverage area, throughput, energy efficiency, quality of service, delay, and outage probability. We provide a detailed discussion for each objective with their constraints, optimization problem, solution approach, and performance metrics. We also provide relationships among different objectives and parameters considered in the literature. Finally, we list open research issues and future research directions to improve UAV‐assisted wireless networks in the context of optimization.

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Section: Delay Minimizationmentioning

confidence: 97%

Section: Research On Enhancing Qos and Delay Minimization In Uav‐assi...mentioning

confidence: 99%

Resource optimization in UAV‐assisted wireless networks—A comprehensive survey

Basharat

Naeem

Qadir

et al. 2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…It is also a key metric in UAV communication systems, as it measures the time taken for a packet to be transmitted from the source UAV to the target UAV [81], including all the processing and transmission delays along the way. The propagation delay is termed as time taken for the signal to travel from the source to destination UAV, mainly defined by the distance of these two UAVs.…”

Section: Average End-to-end Delaymentioning

confidence: 99%

A Survey on UAV Network for Secure Communication and Attack Detection: A focus on Q-learning, Blockchain, IRS and mmWave Technologies

2024

KSII TIIS

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Unmanned Aerial Vehicle (UAV) networks, also known as drone networks, have gained significant attention for their potential in various applications, including communication. UAV networks for communication involve using a fleet of drones to establish wireless connectivity and provide communication services in areas where traditional infrastructure is lacking or disrupted. UAV communication networks need to be highly secured to ensure the technology's security and the users' safety. The proposed survey provides a comprehensive overview of the current state-of-the-art UAV network security solutions. In this paper, we analyze the existing literature on UAV security and identify the various types of attacks and the underlying vulnerabilities they exploit. Detailed mitigation techniques and countermeasures for the protection of UAVs are described in this paper. The survey focuses on the implementation of novel technologies like Q-learning, blockchain, IRS, and mmWave. This paper discusses network simulation tools that range in complexity, features, and programming capabilities. Finally, future research directions and challenges are highlighted.

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“…Every data transmission will face a delay throughout its route of it. The end-to-end delay is the ratio of the difference between received and transmitted time to the total number of packets received [28].…”

Section: ) End-to-end Delaymentioning

confidence: 99%

Quad-Interleaving Routing Algorithm for Performance Enhancement of Oil and Gas Pipeline Network Monitoring

Rajamohan¹,

Subramaniam²,

Feroz³

et al. 2023

IJETAE

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The pipeline is one of the main modes oftransportation for the oil and gas industry that could be laid offshore and onshore. Pipeline transportation requires close monitoring as a failure in pipelines causes disruption of supply, loss of precious commodities and not to mention irreversible environmental damage will be an essential topic. The major issue in AODV and DSDV is when the network gets more extensive, which causes high packet traffic resulting in high packet loss, energy consumption and passive nodes. This research aims to establish a routing algorithm with better performance focusing on throughput, fairness index, delivery ratio and passive nodes and energy consumption. The study is confined to wireless sensor network simulation on Network Simulator Tool. A technique of quad-interleaving Ad-hoc On- demand Distance Vector (QAODV) routing algorithm has been developed where predefined Alpha, Beta, Charlie and Delta nodes will communicate with the nodes which belong to their family. The results of the developed routing protocol have been compared with standard AODV, DSDV and OLSR routing protocols. The developed routing algorithm has produced a massive improvement in the delivery ratio (25% more), throughput (44% more), passive nodes (71 less), fairness index (0.06 more) and energy consumption (0.22J less).

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End-to-End Delay Analysis in Aerial-Terrestrial Heterogeneous Networks

Cited by 11 publications

References 40 publications

Resource optimization in UAV‐assisted wireless networks—A comprehensive survey

Resource optimization in UAV‐assisted wireless networks—A comprehensive survey

A Survey on UAV Network for Secure Communication and Attack Detection: A focus on Q-learning, Blockchain, IRS and mmWave Technologies

Quad-Interleaving Routing Algorithm for Performance Enhancement of Oil and Gas Pipeline Network Monitoring

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