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    PERFORMANCE OF QUEUE MANAGEMENT ALGORITHM IN LTE NETWORK UNDER DDOS ATTACKS
    (2022-01) Ali Said, Aden
    Cellular networks are rapidly evolving to meet the ever-increasing need for data speeds and to offer more services to mobile users everywhere. The fourth generation Long Term Evolution (LTE) network makes a significant contribution to improving the efficiency of cellular networks. Increasing demands on existing cellular networks cause an increase in mobile traffic. This traffic is mainly generated by users equipped with smartphones, tablets and other mobile devices. LTE networks are trying to adapt to this ever-increasing number of mobile users and to offer them a higher quality service. One of the most critical considerations for cellular network operators is whether their networks have efficient mechanisms and can manage them effectively to ensure optimal performance. One of the important elements that endanger network security in cellular networks is Distributed Denial of Service (DDoS) attacks. These attacks cause many problems such as disabling the network, causing it to work below its capacity, disconnecting and dropping the user from the network. Active queue management algorithms (AQM) working in the Radio link control (RLC) layer of the LTE network can predict congestion, provide solutions against possible network attacks, and effectively solve the network congestion problem by reducing the transmission packet rate. The performance of AQM is directly affected by parameters such as end-to-end transfer rate, end-to-end delay, packet delivery rate and fairness index. In this thesis, the performance of queue management algorithms such as RED, CoDel, PIE, pFIFO and Drop-Tail operating in the RLC layer of the cellular LTE network were compared in terms of end-to-end transfer rate, delay, packet delivery rate and fairness index values under DDoS attacks. The CoDel algorithm produced a better result than RED, PIE, pFIFO and DropTail algorithms, with the mechanism of early detection of packet drops.