A Review on Various Routing Protocol Designing Features for Flying Ad Hoc Networks

Ananthi, J. Vijitha; Jose, P. Subha Hency

doi:10.1007/978-981-16-1866-6_23

Cited by 15 publications

(6 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, geographic position mobility-oriented routing (GPMOR) utilizes a prediction algorithm in order to designate the next forwarding UAV based on a Gauss-Markov mobility model [437]. In addition to the Generic algorithms, further QoS algorithms might be investigated by leveraging hybrid routing protocols to find the best path [438]. Delay is another important factor that affects the QoS.…”

Section: A Future Directions For Uav-assisted Wireless Networkmentioning

confidence: 99%

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

et al. 2022

View full text Add to dashboard Cite

The use of drones, formally known as unmanned aerial vehicles (UAVs), has significantly increased across a variety of applications over the past few years. This is due to the rapid advancement towards the design and production of inexpensive and dependable UAVs and the growing request for the utilization of such platforms particularly in civil applications. With their intrinsic attributes such as high mobility, rapid deployment and flexible altitude, UAVs have the potential to be utilized in many wireless system applications. On the one hand, UAVs are able to operate as flying mobile terminals within wireless/cellular networks to support a variety of missions such as goods delivery, search and rescue, precision agriculture monitoring, and remote sensing. On the other hand, UAVs can be utilized as aerial base stations to increase wireless communication coverage, reliability, and the capacity of wireless systems without additional investment in wireless systems infrastructure. The aim of this article is to review the current applications of UAVs for civil and commercial purposes. The focus of this paper is on the challenges and communication requirements associated with UAV-based communication systems. This article initially classifies UAVs in terms of various parameters, some of which can impact UAVs' communication performance. It then provides an overview of aerial networking and investigates UAVs routing protocols specifically, which are considered as one of the challenges in UAV communication. This article later investigates the use of UAV networks in a variety of civil applications and considers many challenges and communication demands of these applications. Subsequently, different types of simulation platforms are investigated from a communication and networking viewpoint. Finally, it identifies areas of future research.

show abstract

Section: A Future Directions For Uav-assisted Wireless Networkmentioning

confidence: 99%

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The routing phase is used to find the efficient path by using an artificial bee colony algorithm on the internet of unmanned aerial vehicles (Ananthi and Subha Hency Jose, 2021, 2022; Jacob and Ebby Darney, 2021; Haoxiang and Smys Smys, 2020; Ananthi and Jose, 2021) (IoUAV). In the routing phase, unmanned aerial vehicles search the shortest route by using an artificial bee colony algorithm.…”

Section: Proposed Techniquementioning

confidence: 99%

Optimal design of artificial bee colony based UAV routing (ABCUR) algorithm for healthcare applications

Ananthi

Jose

2022

IJIUS

Self Cite

View full text Add to dashboard Cite

PurposeTo avoid this situation, the authors proposed an optimal artificial bee colony algorithm-based Unmanned Aerial Vehicle (UAV) routing algorithm for efficient data communication between doctors and patients. This proposed method worked in three stages.Design/methodology/approachIn recent decades, wireless body area networks have played an important role in health care applications. It facilitates the transmission of the patients' health data analysis report to the appropriate doctors.FindingsIn the first phase, biological sensors are connected to the human body via a controller node and collected data is transmitted via Bluetooth to the Personal Device Assistant (PDA). In the second phase, collected data will be transmitted via the Internet of things using an artificial bee colony algorithm. The second aids in determining the best route. In the third phase, unmanned aerial vehicles will use the best path to send collected data to doctors, caregivers, ambulances and cloud storage servers.Originality/valueThe simulation results show that the network's performance is superior when compared to existing approaches. The proposed algorithm achieves a high throughput, a lower delay, a higher link rate and a higher delivery rate.

show abstract

“…Therefore, this issue must be considered when designing a routing scheme for this network 21 , 22 . The most common routing protocols are static routing 23 , 24 , proactive routing 23 , 24 , reactive routing 23 , 24 , hybrid routing 25 , 26 , geographical routing 23 , 24 , and multi-path routing 25 , 27 . The performance of a routing protocol depends on selecting the optimal route, which can be calculated based on various criteria, for example, speed, energy, link lifetime, network traffic, delay, link quality, and movement direction 25 , 28 .…”

Section: Introductionmentioning

confidence: 99%

An energy-aware routing method using firefly algorithm for flying ad hoc networks

Lánský

Rahmani

Malik

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Flying ad-hoc networks (FANETs) include a large number of drones, which communicate with each other based on an ad hoc model. These networks provide new opportunities for various applications such as military, industrial, and civilian applications. However, FANETs have faced with many challenges like high-speed nodes, low density, and rapid changes in the topology. As a result, routing is a challenging issue in these networks. In this paper, we propose an energy-aware routing scheme in FANETs. This scheme is inspired by the optimized link state routing (OLSR). In the proposed routing scheme, we estimate the connection quality between two flying nodes using a new technique, which utilizes two parameters, including ratio of sent/received of hello packets and connection time. Also, our proposed method selects multipoint relays (MPRs) using the firefly algorithm. It chooses a node with high residual energy, high connection quality, more neighborhood degree, and higher willingness as MPR. Finally, our proposed scheme creates routes between different nodes based on energy and connection quality. Our proposed routing scheme is simulated using the network simulator version 3 (NS3). We compare its simulation results with the greedy optimized link state routing (G-OLSR) and the optimized link state routing (OLSR). These results show that our method outperforms G-OLSR and OLSR in terms of delay, packet delivery rate, throughput, and energy consumption. However, our proposed routing scheme increases slightly routing overhead compared to G-OLSR.

show abstract

A Review on Various Routing Protocol Designing Features for Flying Ad Hoc Networks

Cited by 15 publications

References 33 publications

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

Optimal design of artificial bee colony based UAV routing (ABCUR) algorithm for healthcare applications

An energy-aware routing method using firefly algorithm for flying ad hoc networks

Contact Info

Product

Resources

About