EMASS: A Novel Energy, Safety and Mobility Aware-based Clustering Algorithm for FANETs

Aissa, Mohamed
Abdelhafidh, Maroua
Mnaouer, Adel Ben
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Institute of Electrical and Electronics Engineers Inc.
The Unmanned Aerial Vehicles (UAVs), organized as a Flying Ad-hoc NETwork (FANET), are used to make effective remote monitoring in diverse applications. Due to their high mobility, their energy consumption is increasingly affected leading to reduced network stability and communication efficiency. The design of node clustering of a FANET needs to consider the number of UAVs in the vicinity (transmission range) in order to ensure an adaptive reliable routing. Novel clustering schemes have been employed to deal with the highly dynamic flying behavior of UAVs and to maintain network stability. In this context, a new clustering algorithm is proposed to address the fast mobility of UAVs and provide safe inter-UAV distance, stable communication and extended network lifetime. The main contributions of this paper are first to extend and improve important metrics used in two well-known algorithms in the literature namely: The Bio-Inspired Clustering Scheme for FANETs (BICSF) and the Energy Aware Link-based Clustering (EALC). Then, exploiting the improved metrics, a Energy and Mobility-aware Stable and Safe Clustering (EMASS) algorithm, built upon new schemes useful for ensuring stability and safety in FANETs, is proposed.The simulation results showed that the EMASS algorithm outperformed the BICSF and the EALC algorithms in terms of better cluster stability, guaranteed safety, higher packet deliverability, improved energy saving and lower delays. CCBYNCND
This article is not available at CUD collection. The version of scholarly record of this article is published in IEEE Access (2021), available online at: https://doi.org/10.1109/ACCESS.2021.3097323
Ad hoc networks, Clustering algorithm, Clustering algorithms, Energy consumption, Flying Ad-hoc NETwork (FANET), Mobility, Network topology, Reliability, Routing, Routing protocols, Safe-inter-UAV distance, Stability, Stability criteria, Unmanned Aerial Vehicle (UAV)
Aissa, M., Abdelhafidh, M., Abdelhafidh, M., & Mnaouer, A. B. (2021). EMASS: A novel energy, safety and mobility aware-based clustering algorithm for FANETs. IEEE Access, 9, pp. 105506 - 105520. https://doi.org/10.1109/ACCESS.2021.3097323