Improved Sequencing Heuristic DSDV Protocol Using Nomadic Mobility Model for FANETS

Khan, Inam Ullah; Hassan, Muhammad Abul; Fayaz, Muhammad; Gwak, Jeonghwan; Aziz, Muhammad Adnan

doi:10.32604/cmc.2022.020697

Cited by 14 publications

(3 citation statements)

References 17 publications

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“…However, many researchers have made targeted improvements to traditional routing protocols based on FANET characteristics. For example, the DSDV protocol needs to consider the effects of factors such as the limited energy of UAV nodes and link quality, and Khan et al [31] introduced the Bellman-Ford algorithm to improve it based on DSDV. Zhang et al [32] proposed SAP-DSDV, which automatically adjusts the routing update period through the link stability between UAV nodes.…”

Section: Topology-basedmentioning

confidence: 99%

UAV Ad Hoc Network Routing Algorithms in Space–Air–Ground Integrated Networks: Challenges and Directions

Zhang

Igorevich

et al. 2023

Drones

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With the rapid development of 5G and 6G communications in recent years, there has been significant interest in space–air–ground integrated networks (SAGINs), which aim to achieve seamless all-area, all-time coverage. As a key component of SAGINs, flying ad hoc networks (FANETs) have been widely used in the agriculture and transportation sectors in recent years. Reliable communication in SAGINs requires efficient routing algorithms to support them. In this study, we analyze the unique communication architecture of FANETs in SAGINs. At the same time, existing routing protocols are presented and clustered. In addition, we review the latest research advances in routing algorithms over the last five years. Finally, we clarify the future research trends of FANET routing algorithms in SAGINs by discussing the algorithms and comparing the routing experiments with the characteristics of unmanned aerial vehicles.

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Section: Topology-basedmentioning

confidence: 99%

UAV Ad Hoc Network Routing Algorithms in Space–Air–Ground Integrated Networks: Challenges and Directions

Zhang

Igorevich

et al. 2023

Drones

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“…This study covered the issue of energy conservation for flying IoT. A unique DSDV routing scheme for the Internet of Flying Vehicles was presented in this study [30].…”

Section: Related Workmentioning

confidence: 99%

Energy Based Random Repeat Trust Computation in Delay Tolerant Network

Dheenathayalan¹,

Paramasivan²

2023

Computer Systems Science and Engineering

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As the use of mobile devices continues to rise, trust administration will significantly improve security in routing the guaranteed quality of service (QoS) supply in Mobile Ad Hoc Networks (MANET) due to the mobility of the nodes. There is no continuance of network communication between nodes in a delay-tolerant network (DTN). DTN is designed to complete recurring connections between nodes. This approach proposes a dynamic source routing protocol (DSR) based on a feed-forward neural network (FFNN) and energybased random repetition trust calculation in DTN. If another node is looking for a node that swerved off of its path in this situation, routing will fail since it won't recognize it. However, in the suggested strategy, nodes do not stray from their pathways for routing. It is only likely that the message will reach the destination node if the nodes encounter their destination or an appropriate transitional node on their default mobility route, based on their pattern of mobility. The EBRRTC-DTN algorithm (Energy based random repeat trust computation) is based on the time that has passed since nodes last encountered the destination node. Compared to other existing techniques, simulation results show that this process makes the best decision and expertly determines the best and most appropriate route to send messages to the destination node, which improves routing performance, increases the number of delivered messages, and decreases delivery delay. Therefore, the suggested method is better at providing better QoS (Quality of Service) and increasing network lifetime, tolerating network system latency.

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“…Therefore, UAVs actively plays important role in smart cities. DSDV routing protocol is having the process of incremental updates which is helpful to improve and secure communication standards in UAV enabled smart cities [14]. Moreover, for secure communication protocols need to be designed to mitigate related problems of the network [15].…”

Section: Literature Studymentioning

confidence: 99%

Detection of Cyber Attacks using Machine Learning ‎based Intrusion Detection System for IoT Based Smart ‎Cities

Chohan,

Haider,

Muhammad Yaseen Ayub

et al. 2023

EAI Endorsed Trans Smart Cities

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The world’s dynamics is evolving with artificial intelligence (AI) and the results are smart products. A smart city has smart city is collection of smart innovations powered with AI and internet of things (IoTs). Along with the ease and comfort that the concept of a smart city pointed at, many security concerns are being raised that hinders the path of its flourishment. An Intrusion Detection System (IDS) monitors the whole network traffic and alerts in case of any anomaly. A Machine Learning-based IDS intelligently senses the network threats, takes decisions about data packet legibility and alarm the user. Researchers have deployed various ML techniques to IDS to improve the detection accuracy. This work presents a comparative analysis of various ML algorithms trained over UNSW-NB15 dataset. ADA Boost, Linear Support Vector Machine (LSVM), Auto Encoder Classifier, ‎Quadratic Support Vector Machine (QSVM) and Multi-Layer Perceptron algorithms are being employed in the stimulation. ADA Boost showed an excellent accuracy of 98.3% in the results.

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Improved Sequencing Heuristic DSDV Protocol Using Nomadic Mobility Model for FANETS

Cited by 14 publications

References 17 publications

UAV Ad Hoc Network Routing Algorithms in Space–Air–Ground Integrated Networks: Challenges and Directions

UAV Ad Hoc Network Routing Algorithms in Space–Air–Ground Integrated Networks: Challenges and Directions

Energy Based Random Repeat Trust Computation in Delay Tolerant Network

Detection of Cyber Attacks using Machine Learning ‎based Intrusion Detection System for IoT Based Smart ‎Cities

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