OLSR+: A new routing method based on fuzzy logic in flying ad-hoc networks (FANETs)

Rahmani, Amir Masoud; Ali, Saqib; Yousefpoor, Efat; Yousefpoor, Mohammad Sadegh; Javaheri, Danial; Lalbakhsh, Pooia; Ahmed, Omed Hassan; Hosseinzadeh, Mehdi; Lee, Sang‐Woong

doi:10.1016/j.vehcom.2022.100489

Cited by 28 publications

(15 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For proactive routing, the geographical information of neighboring UAVs is exploited to select a reliable MPR. 52,53 However, in this routing category, decisions made by greedy forwarding may not be optimal due to the consideration of only geographical information. Moreover, the delay induced by the route discovery process and the failure of greedy forwarding makes them unsuitable for time-critical applications.…”

Section: Hybrid Routingmentioning

confidence: 99%

MF‐DLB: Multimetric forwarding and directed acyclic graph‐based load balancing for geographic routing in FANETs

Singh,

Sharma,

Verma

2024

Concurrency and Computation

View full text Add to dashboard Cite

SummaryFlying ad hoc network (FANET) comprising unmanned aerial vehicles (UAVs) emerges as a promising solution for numerous military and civil applications. Transferring data collected from the environment to the ground station (GS) is a primary concern for meeting the communication demands of most of these applications. However, the highly mobile UAVs with limited communication range, resulting in frequent topology change and intermittent connectivity, make data routing challenging. In such scenarios, geographic routing is a viable solution due to its scalability and robustness. However, the basic forwarding mechanism of geographic routing favors the neighboring UAV nearest to the destination, impacted substantially by link failures and routing holes in a dynamic environment. Additionally, routing decisions ignoring the current load over UAVs contribute to performance degradation due to the high concentration of data traffic near the GS. Thus, to address these issues, a geographic routing protocol named MF‐DLB comprising multimetric forwarding (MF) and a directed acyclic graph‐based load balancing (DLB) scheme is proposed to enhance packet forwarding in FANETs. MF takes account of multiple metrics related to connectivity, geographic progress, link lifetime, and residual energy to select the next hop with a stable communication link while effectively bypassing the routing holes. The second scheme, DLB, focuses on proactively maintaining routing paths near GS for load distribution among underutilized nodes to address the congestion problem. Simulations performed in network simulator ns‐3 confirm the outperformance of MF‐DLB over other related routing schemes in terms of different performance metrics.

show abstract

Section: Hybrid Routingmentioning

confidence: 99%

MF‐DLB: Multimetric forwarding and directed acyclic graph‐based load balancing for geographic routing in FANETs

Singh,

Sharma,

Verma

2024

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…Among various types of OLSR algorithms, energyefficient and sturdy routes are formed in the network with OLSR+, an improved fuzzy logic-based OLSR algorithm [37]. Among the four phases of OLSR+, the discovery of neighboring nodes is its first phase.…”

Section: A: Flat Routing Protocolsmentioning

confidence: 99%

Optimized Routing of UAVs Using Bio-Inspired Algorithm in FANET: A Systematic Review

et al. 2023

View full text Add to dashboard Cite

Flying Ad hoc Network (FANET) is a self-organizing wireless network that constitutes swarms of flying nodes, namely Unmanned Aerial Vehicles (UAV), and communicates in close proximity. It has various distinguishing characteristics that set it apart from other ad hoc networks, posing some issues, particularly in routing. UAVs are highly dynamic and have frequent topology changes. Hence, the network urges an efficient routing technique to coordinate the node swarms and enhance the evaluation metrics of the network. The biological behavior of various living organisms, such as animals, insects, microbes, and humans, inspires researchers to solve various routing problems in ad hoc networks. Decentralized self-organized swarms of UAVs closely resemble the biological system. Therefore, the Bio-Inspired Algorithms (BIA) resolve a wide range of routing challenges in FANET. A Systematic Literature Review (SLR) is adopted to survey FANET routing methods based on non-hybrid and hybrid BIAs to properly comprehend the existing bio-inspired strategies used in FANET routing. The review will be beneficial for the researchers in the specified area. To our knowledge, no SLR has been conducted about the FANET routing protocol that employs BIA. This paper examines (1) the characteristics and features of existing routing algorithms, (2) the need of both non-hybrid and hybrid BIA for effective and optimal routing, (3) an analysis of the method's simulation tools, evaluation metrics, and mobility models, (4) the current issues and scope of the study related to the specified method.INDEX TERMS Bio-Inspired Algorithm (BIA), Flying Ad hoc Networks (FANET), Metaheuristic optimization, Systematic Literature Review (SLR), Unmanned Aerial Vehicle (UAV).

show abstract

“…Rahmani et al 34 presented a fuzzy-based routing protocol called OLSR+ for flying ad hoc networks. It is an improved version of the optimized link state routing protocol (OLSR).…”

Section: Related Workmentioning

confidence: 99%

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

Lánský

Rahmani

Malik

et al. 2023

Sci Rep

Self Cite

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

OLSR+: A new routing method based on fuzzy logic in flying ad-hoc networks (FANETs)

Cited by 28 publications

References 37 publications

MF‐DLB: Multimetric forwarding and directed acyclic graph‐based load balancing for geographic routing in FANETs

MF‐DLB: Multimetric forwarding and directed acyclic graph‐based load balancing for geographic routing in FANETs

Optimized Routing of UAVs Using Bio-Inspired Algorithm in FANET: A Systematic Review

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

Contact Info

Product

Resources

About