QoS and QoE Aware Routing Protocol for Flying Ad-Hoc Surveillance Networks Using Fuzzy Inference Systems

Souza, Jorge; Jailton, José; Carvalho, Tássio; Araújo, Jasmine; Francês, Renato

doi:10.1590/2179-10742020v19i11842

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Journal of Microwaves, Optoelectronics and Electromagnetic Applications

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Article • J. Microw. Optoelectron. Electromagn. Appl. 19 (1) • Mar 2020 • https://doi.org/10.1590/2179-10742020v19i11842 copy

QoS and QoE Aware Routing Protocol for Flying Ad-Hoc Surveillance Networks Using Fuzzy Inference Systems

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

The Flying Ad-hoc Network (FANET) networks have often operated in regions that are difficult to reach and have no fixed infrastructure. The use of devices such as Unmanned Aerial Vehicles (UAV) enable aerial networks to be created that are extremely fast, although there are no specific routing protocols for this type of network that can make communication more efficient among these devices. For this reason, this paper sets out a specific routing protocol for FANET networks that is designed for the discovery of routes among UAV devices. Evidence of the benefits of this strategy has been obtained through simulation by the Network Simulator version 2.

Index Terms
FANET; Flight Autonomy; Quality of Experience; Routing Protocol; Fuzzy System

Proposal	Flight Autonomy	Decision Strategy	Proposal Focus
[⁴4 Mavic 2 Pro Zoom User Manual V 2.0. (2019). Accessed: Jan. 10, 2019. [Online]. Available: https://dl.djicdn.com/downloads/Mavic_2/20190417/Mavic_2_Pro_Zoom_User_Manual_v2.0_en.pdf https://dl.djicdn.com/downloads/Mavic_2/... ]	No	To use Gauss-Markov Mobility Model	Evaluate traditional routing protocol in FANETs
[⁵5 S. Winkler, “Perceptual video quality metrics - a review,” in Digital Video Image Quality and Perceptual Coding, CRC Press, 2005.]	No	Mechanism for data routing based on localization	The position for UAV's device
[⁶6 Z. Zheng, A. Sangaiah, T. Wang, “Adaptive Communication Protocols in Flying Ad Hoc Network,” IEEE Communications Magazine, vol. 56, no. 1, Jan. 2018.]	No	Extension of OLSR protocol called P-OLSR	Compare P-OLSR with OLSR
[⁷7 D. S. Vasiliev, D. S. Meitis, A. Abilov, “Simulation-Based Comparison of AODV, OLSR and HWMP Protocols for Flying Ad Hoc Networks,” in Balandin S., Andreev S., Koucheryavy Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and System, 2014, pp. 245-252, doi: 10.1007/978-3-319-10353-2_21. https://doi.org/10.1007/978-3-319-10353-... ]	No	Energy -efficiency algorithm.	To reduce the energy consumption
[⁸8 F. Khelifi, A. Bradai, K. Singh and M. Atri, “Localization and Energy-Efficient Data Routing for Unmanned Aerial Vehicles: Fuzzy-Logic-Based Approach,” IEEE Communications Magazine, vol. 56, no. 4, pp. 129-133, Apr. 2018.]	No	Survey of the routing protocols	Improve the routing performance
[⁹9 A. Nayyar, “Flying Adhoc Network (FANETs): Simulation Based Performance Comparison of Routing Protocols: AODV, DSDV, DSR, OLSR, AOMDV and HWMP,” in Int. Conf. on Advances in Big Data, Computing and Data Communication Systems (icABCD), Durban, 2018, pp. 1-9.]	No	Discuss the hop-by-hop communication	Number of UAV's necessary
Current Proposal	Yes	Routing Protocol with Fuzzy Logic System	Selecting the best routing communication considering Flight Autonomy with mobility and RSSI

Mobility	Flight Autonomy	RSSI	Output
LOW	MEDIUM	MEDIUM	GOOD
LOW	HIGH	MEDIUM	GOOD
MEDIUM	MEDIUM	MEDIUM	GOOD
MEDIUM	HIGH	MEDIUM	GOOD
LOW	MEDIUM	HIGH	EXCELENT
LOW	HIGH	HIGH	EXCELENT
MEDIUM	HIGH	HIGH	EXCELENT

Parameter	Value
Drones	10
Access Technology	IEEE 802.11g
Propagation Model	Shadowing
Mobility type	Random Waypoint
Query	Droptail
Number of Simulations	100
Confidence Interval	95 %
Frequency	2.4 GHz
Area	200m x 200m

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