Design a novel routing protocol for flying ad hoc networks based on fuzzy inference to enhance quality of service

The emergence of flying ad hoc networks (FANETs) has enabled new forms of communication for unmanned aerial vehicles (UAVs), including surveillance; emergency response; environmental monitoring; and military operations. However, due to their high degree of mobility and dynamic topology, as well as the lack of reliability associated with both communication links and route failure, along with limited communication resources and diverse network conditions, finding reliable routes within FANETs is an extremely difficult problem. As a result, many traditional routing protocols will degrade significantly in terms of their ability to provide good service in very mobile FANET environments; therefore, they can be expected to increase routing delay; produce higher amounts of routing overhead; and cause packets to become lost or delayed while traveling through the network. This research presents a unique Fuzzy-Inference-System (FIS)-based AODV Routing Protocol for use on highly-mobile FANETs, which combines the capabilities of a Fuzzy Inference System (FIS) with the Ad-hoc On-demand Distance Vector (AODV) routing protocol. The proposed method uses three parameters—UAV Mobility, Channel Utilization, and Queue Utilization—as inputs to determine route quality and then choose the most viable communication path. Additionally, the proposed protocol includes an adaptive Route Maintenance Mechanism that improves route reliability and reduces congestion throughout the network. The proposed protocol was tested via NS-2 simulations and compared with OLSR and Adaptive-FANET routing methods, each operating at various levels of UAV density. Results from these experiments show improved Packet Delivery Performance (PDP); Throughput; Routing Overhead; and Network Delay. The Fuzzy-based Routing Strategy also effectively manages available network resources to enhance Quality of Service (QoS). Overall, the experimental results clearly indicated that the proposed Fuzzy-AODV protocol provides a reliable and effective routing method for highly-dynamic FANET environments.

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Publication Details

Journal
Discover Artificial Intelligence
Published
2026-10-07
DOI
https://doi.org/10.1007/s44163-026-02165-4
Primary Topic
Mobile Ad Hoc Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Design a novel routing protocol for flying ad hoc networks based on fuzzy inference to enhance quality of service

Shaila Chugh, Manish Rai, Praveen Kumar Mannepalli, Shiv Shakti Shrivastava et al.
Discover Artificial Intelligence
Mobile Ad Hoc Networks
article

Design a novel routing protocol for flying ad hoc networks based on fuzzy inference to enhance quality of service

Shaila Chugh, Manish Rai, Praveen Kumar Mannepalli, Shiv Shakti Shrivastava, Parag Sohoni
article en

Abstract

The emergence of flying ad hoc networks (FANETs) has enabled new forms of communication for unmanned aerial vehicles (UAVs), including surveillance; emergency response; environmental monitoring; and military operations. However, due to their high degree of mobility and dynamic topology, as well as the lack of reliability associated with both communication links and route failure, along with limited communication resources and diverse network conditions, finding reliable routes within FANETs is an extremely difficult problem. As a result, many traditional routing protocols will degrade significantly in terms of their ability to provide good service in very mobile FANET environments; therefore, they can be expected to increase routing delay; produce higher amounts of routing overhead; and cause packets to become lost or delayed while traveling through the network. This research presents a unique Fuzzy-Inference-System (FIS)-based AODV Routing Protocol for use on highly-mobile FANETs, which combines the capabilities of a Fuzzy Inference System (FIS) with the Ad-hoc On-demand Distance Vector (AODV) routing protocol. The proposed method uses three parameters—UAV Mobility, Channel Utilization, and Queue Utilization—as inputs to determine route quality and then choose the most viable communication path. Additionally, the proposed protocol includes an adaptive Route Maintenance Mechanism that improves route reliability and reduces congestion throughout the network. The proposed protocol was tested via NS-2 simulations and compared with OLSR and Adaptive-FANET routing methods, each operating at various levels of UAV density. Results from these experiments show improved Packet Delivery Performance (PDP); Throughput; Routing Overhead; and Network Delay. The Fuzzy-based Routing Strategy also effectively manages available network resources to enhance Quality of Service (QoS). Overall, the experimental results clearly indicated that the proposed Fuzzy-AODV protocol provides a reliable and effective routing method for highly-dynamic FANET environments.

Discover Artificial IntelligenceVol. 6(1)
Chandigarh University (IN), AISECT University (IN), Parul University (IN), Manipal University Jaipur
Openalex Percentile: Top 11%
Mobile Ad Hoc Networks
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