Using Centrality Based Topology Control for FANET Survivability Against Jamming

T. Tolga Sarı*, Gökhan Seçinti

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

3 Atıf (Scopus)

Özet

Flying Ad Hoc Networks (FANETs) provide connectivity in extreme environments such as battle zones and disaster areas. Since these networks operate without infrastructure, they must calculate routes on the fly. Unfortunately, as each e2e link selfishly chooses the shortest path for its flow, they also tend to overwhelm geographically central nodes, making these nodes the bottleneck for all flows. On top of this, these networks are quite sensitive to jamming attacks, which can shut down the network's operation entirely. In this paper, we extend our previous work CentAir with an additional operation state that enables rapid communication by reducing interframe spaces of nodes according to their eigenvector centrality measure. Following this, we propose an intelligent heuristic to enable hybrid operation among these states. This hybrid operation state improves e2e latency by modifying interframe spacing regarding the node's eigenvector centrality. Our exhaustive simulation results show that Hybrid CentAir achieves an 18.1 percent more throughput, a 21.1 percent lower latency while being 17.8 percent more energy efficient compared to multi-channel OLSR. Additionally, our protocol shows an 11.5 percent better packet delivery ratio against randomly placed deceptive jammers that continuously transmit false packets in the area.

Orijinal dilİngilizce
Makale numarası110250
DergiComputer Networks
Hacim242
DOI'lar
Yayın durumuYayınlandı - Nis 2024

Bibliyografik not

Publisher Copyright:
© 2024 Elsevier B.V.

Finansman

This study is funded by Istanbul Technical University , Department of Scientific Research Projects (ITU-BAP, MCAP-2022-43828). This work is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) 1515 Frontier R&D Laboratories Support Program for BTS Advanced AI Hub: BTS Autonomous Networks and Data Innovation Lab. Project 5239903.

FinansörlerFinansör numarası
Department of Scientific Research Projects
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu5239903
Istanbul Teknik Üniversitesi
Bilimsel Araştırma Projeleri Birimi, İstanbul Teknik ÜniversitesiMCAP-2022-43828

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