An Optimized Communication Scheme for Energy Efficient and Secure Flying Ad-hoc Network (FANET)

Namdev, Mayank; Goyal, Sachin; Agarwal, Ratish

doi:10.1007/s11277-021-08515-y

Cited by 34 publications

(5 citation statements)

References 26 publications

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“…As indicated by reproduction results, GPS parody signs can be identified and dropped with almost 100% high exactness and low correspondence cost. In order to ensure energy-efficient and secure optimal routing in a FANET, a WOA-OLSR algorithm based on the wavelet optimization algorithm is proposed 26 . The best exhibition of this calculation was assessed utilizing different execution boundaries, for example, bundle conveyance rate, delay, energy utilization, throughput and intricacy.…”

Section: Literature Surveymentioning

confidence: 99%

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

Chandrasekar,

Shanmugavalli,

Mahesh

et al. 2024

Sci Rep

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In wireless networking, the security of flying ad hoc networks (FANETs) is a major issue, and the use of drones is growing every day. A distributed network is created by a drone network in which nodes can enter and exit the network at any time. Because malicious nodes generate bogus identifiers, FANET is unstable. In this research study, we proposed a threat detection method for detecting malicious nodes in the network. The proposed method is found to be most effective compared to other methods. Malicious nodes fill the network with false information, thereby reducing network performance. The secure ad hoc on-demand distance vector (AODV) that has been suggested algorithm is used for detecting and isolating a malicious node in FANET. In addition, because temporary flying nodes are vulnerable to attacks, trust models based on direct or indirect reliability similar to trusted neighbors have been incorporated to overcome the vulnerability of malicious/selfish harassment. A node belonging to the malicious node class is disconnected from the network and is not used to forward or forward another message. The FANET security performance is measured by throughput, packet loss and routing overhead with the conventional algorithms of AODV (TAODV) and reliable AODV secure AODV power consumption decreased by 16.5%, efficiency increased by 7.4%, and packet delivery rate decreased by 9.1% when compared to the second ranking method. Reduced packet losses and routing expenses by 9.4%. In general, the results demonstrate that, in terms of energy consumption, throughput, delivered packet rate, the number of lost packets, and routing overhead, the proposed secure AODV algorithm performs better than the most recent, cutting-edge algorithms.

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Section: Literature Surveymentioning

confidence: 99%

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

Chandrasekar,

Shanmugavalli,

Mahesh

et al. 2024

Sci Rep

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“…The algorithms used in UAS are mainly based on AODV for routing operations. In [11], a performance comparison of OLSR and AODV is presented by the authors for flying ad hoc networks (FANETs). They showed that the AODV performs better than the OLSR for low-density and highly dynamic networks.…”

Section: Related Workmentioning

confidence: 99%

A Method to Reduce Route Discovery Cost of UAV Ad Hoc Network

Waqas

Rehman

Dilpazir

et al. 2023

International Journal of Distributed Sensor Networks

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The unmanned aerial vehicle communication networks (UAVCNs) are composed of unmanned aerial vehicles (UAVs) connected in ad hoc mode to facilitate vertical communication in 5G and beyond networks. UAVs operating in an ad hoc mode of operation mostly use reactive routing protocols to establish routes in the network to reduce the energy consumption of the nodes. In this article, a route discovery method is presented to reduce the overhead faced by reactive routing protocols during the route discovery phase. The expanding ring search (ERS) method is mostly used by reactive routing protocols in the destination discovery phase of the routing algorithm. Although the performance of the ERS method is better than simple flooding, the presented method further reduces energy consumption and routing overhead as compared to the conventional ERS method. To achieve the task, the time to live (TTL) is modified to accommodate a large number of nodes in a search attempt. We proposed variants of the proposed techniques for diverse application requirements and compared the performance with the state-of-the-art ERS technique. It has been demonstrated with the help of simulations that the presented algorithm outperforms the ERS method in terms of reduced routing overhead and reduced energy consumption.

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“…In [19], Kiani et al proposed incremental gray wolf optimization (I-GWO) and extended gray wolf optimization (Ex-GWO) for the path planning of agricultural robots to complete various tasks in farmland. In [20], in order to solve problems such as UAV flight time periods, Namdev et al proposed a WOA-OLSR algorithm to optimize the flight self-organizing network to provide energy-saving and safe routing solutions. In [21], Shanshan et al proposed a hybrid genetic algorithm for the optimization of UAV networks to solve the deployment problem of UAVs and thereby improve UAV group coverage.…”

Section: Introductionmentioning

confidence: 99%

A Niche Adaptive Elite Evolutionary Algorithm for the Clustering Optimization of Intelligent Unmanned Agricultural Unmanned Aerial Vehicle Swarm Collaboration Networks

Zhong,

Zhou,

Zhang

2023

Applied Sciences

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Nowadays, the intelligent unmanned agricultural unmanned aerial vehicle (UAV) swarm collaboration network (AUSCN) has fully demonstrated its advantages in agricultural monitoring and management. By using an AUSCN, multi-machine cooperation can be realized to expand the detection range, and more complex tasks can be completed without human participation, so as to improve work efficiency and reduce the consumption of manpower and material resources. In AUSCNs, clustering is a key method to lower energy consumption. However, there is a challenge to select cluster heads in AUSCNs because of the limitation of transmission distances and the complexity of network topological structures. In addition, this problem has been confirmed as NP-hard. In this paper, a new niche adaptive elite evolutionary algorithm (NAEEA) is proposed to solve this problem. NAEEAs can search within various complicated stochastic situations at high speeds with characterized high precision and fast convergence. This algorithm integrates the merits of elite selection and adaptive adjusting to achieve high performance. In NAEEAs, a new adaptive operator is designed to speed up the convergence rate, while a novel elite operator is proposed to avoid local optima and raise the exploration ability. Furthermore, a new niche operator is also proposed to increase the population diversity. The simulation results show that, compared with an evolutionary algorithm (EA), a simulated annealing algorithm (SA) and a leapfrog algorithm (SFLA), clustering energy consumption based on an NAEEA is significantly reduced, and the network energy consumption of the AUSCN is up to 21.43%, 25.00% and 25.76% lower than the other three algorithms, respectively.

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An Optimized Communication Scheme for Energy Efficient and Secure Flying Ad-hoc Network (FANET)

Cited by 34 publications

References 26 publications

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

Secure malicious node detection in flying ad-hoc networks using enhanced AODV algorithm

A Method to Reduce Route Discovery Cost of UAV Ad Hoc Network

A Niche Adaptive Elite Evolutionary Algorithm for the Clustering Optimization of Intelligent Unmanned Agricultural Unmanned Aerial Vehicle Swarm Collaboration Networks

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