School of Engineering, Applied Science and Technology

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Browsing School of Engineering, Applied Science and Technology by Author "Aissa, Mohamed"

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    EMASS: A Novel Energy, Safety and Mobility Aware-based Clustering Algorithm for FANETs
    (Institute of Electrical and Electronics Engineers Inc., 2021) Aissa, Mohamed; Abdelhafidh, Maroua; Mnaouer, Adel Ben
    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
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    Enhanced Fuzzy logic-based Cluster Stability in Vehicular ad hoc Network
    (Institute of Electrical and Electronics Engineers Inc., 2021) Aissa, Mohamed; Bouhdid, Badia; Mnaouer, Adel Ben
    VANET nodes are characterized by their high mobility and they exhibit different mobility patterns. Therefore, VANET clustering schemes should take into consideration the mobility parameters among neighboring nodes to produce relatively stable clustering structure. This paper proposes a novel cluster head selection Fuzzy Logic-based k-hop distributed clustering scheme for VANETs. This scheme considers the safe inter-distance between vehicles as one of important metrics for cluster head selection. Our contribution deals better with the scalability and stability issues of VANETs and can achieve a high stable cluster topology compared to other schemes. These features make the proposed scheme more suitable for VANETs networks. Simulation proves the effectiveness of the new proposed scheme to create stable clusters by reducing re-clustering overhead and prolonging cluster lifetime compared to other existing clustering schemes for VANET. © 2021 IEEE.
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    SOFCluster: Safety-oriented, fuzzy logic-based clustering scheme for vehicular ad hoc networks
    (Wiley Blackwell, 2022-03) Aissa, Mohamed; Bouhdid, Badia; Mnaouer, Adel Ben; Belghith, AissaAbdelfettah; AlAhmadi, Saad
    Vehicular ad hoc network (VANET) nodes are characterized by their high mobility and by exhibiting different mobility patterns. Therefore, VANET clustering schemes are required to account for the mobility parameters among neighboring nodes to produce relatively stable clustering schemes. In this article, we propose a novel cluster-head (CH) selection scheme for VANETs. This scheme is based on a fuzzy logic-powered, k-hop distributed clustering algorithm. It deals efficiently with scalability and stability issues of VANETs and is able to achieve highly stable clustering topologies as compared with other schemes. Our proposed clustering scheme strives to maintain a safe intervehicle distance as a one prime metric for CH selection. Moreover, a major contribution of our work is the proposal of a novel strategy for constructing fuzzy logic-based clustering algorithms useful for VANETs. This proposed solution is useful in an Internet of things-based setting that involves controlled vehicle-to-vehicle communication. We first derive mathematically, a new average distance estimation formula that is used as a metric for selecting CHs, leading to safer clusters that avoid collisions with front and rear vehicles. Furthermore, the new proposed scheme creates stable clusters by reducing reclustering overhead and prolonging clusters' lifetimes. © 2020 John Wiley & Sons, Ltd.