A Simple Proactive Routing Protocol with Multiple Base Stations Deployment for Unmanned Aerial Vehicular Networks

Bahloul, Nour El Houda; Bashir, Nouman; Boudjit, Saâdi; Boubiche, Djallel Eddine

doi:10.1109/giis48668.2019.9044958

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…To ensure a biconnected graph, leaf nodes are moved to cut-vertices that result in an overall increase in connectivity and an entire network's degree of fault-tolerance. A simple Proactive Routing scheme with Multiple ground Base Stations deployment (PRMBS) [13] is a simple routing approach for UAV networks. Periodic Hello messages are broadcast from the BS and flooded in the entire network.…”

Section: Related Workmentioning

confidence: 99%

A Distributed Anticipatory Life- Enhancing Recovery Approach for Unmanned Aerial Vehicular Networks

Bashir

Boudjit

Saidi

2021

2021 IEEE 18th Annual Consumer Communications &Amp; Networking Conference (CCNC)

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Rapidly growing research in the field of Unnamed Aerial Vehicles (UAVs) has redrawn the application map for UAVs that now incorporates personal to public side applications apart from having just military domain within its boundary. Despite numerous practical advantages, UAVs systems are not utilized up to their full potential owing to the characteristics of higher mobility and limited lifetime of on-board batteries. In multi-hop real-time systems, abrupt movement or early depletion of energy resources for some overloaded UAVs may result in the creation of a network hole or even in a breakdown of the whole network. In this article, a new Life-Enhancing recovery Approach for a Multi-UAVs (LEAMU) network is proposed that not only provides a routing solution but also serves as a fail-safe method. The crux of the LEAMU is the identification of the best recovering UAV since the selection of an unhealthy UAV will result in more recovery requests afterward. In LEAMU, network hole creation is avoided beforehand through a distributed election of a suitable candidate keeping distance, remaining energy, neighborhood density, and traffic load factors into consideration. The proposed strategy is simulated and has shown to have a promising future for its integration into the existing UAV systems.

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Section: Related Workmentioning

confidence: 99%

A Distributed Anticipatory Life- Enhancing Recovery Approach for Unmanned Aerial Vehicular Networks

Bashir

Boudjit

Saidi

2021

2021 IEEE 18th Annual Consumer Communications &Amp; Networking Conference (CCNC)

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“…But the limited working period of the UAVs due to the constrained battery capacity is a major challenging issue. When a particular node or UAV fails it is declared as the death of the node and the network is immediately demanded to reorganize its structure to exclude the dead node to establish an uninterrupted network 4 . This requirement demands predictive network design which increases the complexity of the network design 5 .…”

Section: Introductionmentioning

confidence: 99%

“…When a particular node or UAV fails it is declared as the death of the node and the network is immediately demanded to reorganize its structure to exclude the dead node to establish an uninterrupted network. 4 This requirement demands predictive network design which increases the complexity of the network design. 5 The conventional network framework is not considered to be effective for the use of the UAVs as the new network design should consider the factors like increased movement of the nodes and the change in the topology with the death of a node.…”

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confidence: 99%

Topology based energy efficient routing using integration of fuzzy based markov chain cluster‐optimized novel ant bee colony approach in FANET

Ali

Ruby

2022

Concurrency and Computation

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Summary Flying adhoc network (FANET) is a rapidly flourishing technology in recent years which has an excellent scope of growth in the to the improvised mobility and the frequency changing topology FANETs are considered as a challenging technology to design an optimal network model. This problem is fixed with the topology based routing technique. Hence a novel hybrid clustering algorithm where fuzzy based Markov chain cluster (FMC2) is integrated with the optimized novel ant bee colony (ONABC) optimization algorithm (IoFMC2‐ONABC). This algorithm demonstrates an improvised efficiency with the novel ant bee colony algorithm. The proposed model simulation is done in an NS‐2 simulator and results are compared against the existing conventional approaches like adhoc on‐demand distance vector, efficient intelligent packet broadcasting protocol, energy‐efficient routing in flying ad hoc networks, and energy‐efficient gray wolf. This method aims at achieving improvised connectivity, optimizing the power consumption thereby increasing the residual energy augmenting the performance efficiency of the network through selection of the proper cluster center during each transmission. Thus the energy consumption of the node was optimized to 7.6 J with the highest packet delivery ratio of about 85.15 ensuring minimal packet losses during huge data transmission.

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A Simple Proactive Routing Protocol with Multiple Base Stations Deployment for Unmanned Aerial Vehicular Networks

Cited by 2 publications

References 17 publications

A Distributed Anticipatory Life- Enhancing Recovery Approach for Unmanned Aerial Vehicular Networks

A Distributed Anticipatory Life- Enhancing Recovery Approach for Unmanned Aerial Vehicular Networks

Topology based energy efficient routing using integration of fuzzy based markov chain cluster‐optimized novel ant bee colony approach in FANET

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