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

Souza, Jorge A. M. de; Jailton, José; Carvalho, Tássio; Araújo, Jasmine Priscyla Leite de; Francês, Carlos Renato Lisboa

doi:10.1590/2179-10742020v19i11842

Cited by 2 publications

(1 citation statement)

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“…The reward for reinforcement learning was on maximization of packet delivery ratio, without consideration for factors like delay, overhead www.ijacsa.thesai.org reduction etc. Souza et al [22] used fuzzy logic to improve the route discovery process in FANET. The routing decision is based on received signal strength indicator and mobility level.…”

Section: Related Workmentioning

confidence: 99%

Routing with Multi-Criteria QoS for Flying Ad-hoc Networks (FANETs)

Reddy¹,

Sekhar²

2022

IJACSA

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Flying Ad-hoc Network (FANET) is a type of Adhoc network on backbone of Unmanned Aerial Vehicle (UAV). These networks are used for providing communication services in case of natural disasters. Dynamic changes in link quality and mobility distort the Quality of Service (QoS) for routing in FANETs. This work proposed a Multi Criteria QoS Optimal Routing (MCQOR) guided by prediction of link quality and three-dimensional (3D) movement of FANET nodes. The network is clustered based on prediction of movement of nodes. Over the clustered topology, routing path is selected in reactive manner with joint optimization of packet delivery ratio, delay, and network overhead. In addition, cross layer feedback is used to reduce the packet generation rate and congestion in network.Through simulation analysis, the proposed routing protocol is found to have 3.8% higher packet delivery ratio, 26% lower delay and 14% lower network overhead compared to existing works.

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Section: Related Workmentioning

confidence: 99%