scholarly journals A review on Queue Management Algorithms in Large Networks

2021 ◽  
Vol 1076 (1) ◽  
pp. 012034
Author(s):  
Mustafa Maad Hamdi ◽  
Hussain Falih Mahdi ◽  
Mohammed Salah Abood ◽  
Ruaa Qahtan Mohammed ◽  
Abdulkareem Dawah Abbas ◽  
...  
2021 ◽  
Author(s):  
Minsu Kim

Internet of Things (IoT) has pervaded most aspects of our life through the Fourth Industrial Revolution. It is expected that a typical family home could contain several hundreds of smart devices by 2022. Current network architecture has been moving to fog/edge architecture to have the capacity for IoT. However, in order to deal with the enormous amount of traffic generated by those devices and reduce queuing delay, novel self-learning network management algorithms are required on fog/edge nodes. For efficient network management, Active Queue Management (AQM) has been proposed which is the intelligent queuing discipline. In this paper, we propose a new AQM based on Deep Reinforcement Learning (DRL) to handle the latency as well as the trade-off between queuing delay and throughput. We choose Deep Q-Network (DQN) as a baseline of our scheme, and compare our approach with various AQM schemes by deploying them on the interface of fog/edge node in IoT infrastructure. We simulate the AQM schemes on the different bandwidth and round trip time (RTT) settings, and in the empirical results, our approach outperforms other AQM schemes in terms of delay and jitter maintaining above-average throughput and verifies that DRL applied AQM is an efficient network manager for congestion.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yuanlong Cao ◽  
Ruiwen Ji ◽  
Lejun Ji ◽  
Mengshuang Bao ◽  
Lei Tao ◽  
...  

With the development of social networks, more and more mobile social network devices have multiple interfaces. Multipath TCP (MPTCP), as an emerging transmission protocol, can fit multiple link bandwidths to improve data transmission performance and improve user experience quality. At the same time, due to the large-scale deployment and application of emerging technologies such as the Internet of Things and cloud computing, cyber attacks against MPTCP have gradually increased. More and more network security research studies point out that low-rate distributed denial of service (LDDoS) attacks are relatively popular and difficult to detect and are recognized as one of the most severe threats to network services. This article introduces six classic queue management algorithms: DropTail, RED, FRED, REM, BLUE, and FQ. In a multihomed network environment, we perform the performance evaluation of MPTCP under LDDoS attacks in terms of throughput, delay, and packet loss rate when using the six algorithms, respectively, by simulations. The results show that in an MPTCP-enabled multihomed network, different queue management algorithms have different throughput, delay, and packet loss rate performance when subjected to LDDoS attacks. Considering these three performance indicators comprehensively, the FRED algorithm has better performance. By adopting an effective active queue management (AQM) algorithm, the MPTCP transmission system can enhance its robustness capability, thus improving transmission performance. We suggest that when designing and improving the queue management algorithm, the antiattack performance of the algorithm should be considered: (1) it can adjust the traffic speed by optimizing the congestion control mechanism; (2) the fairness of different types of data streams sharing bandwidth is taken into consideration; and (3) it has the ability to adjust the parameters of the queue management algorithm in a timely and accurate manner.


Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2324 ◽  
Author(s):  
Mykola Beshley ◽  
Natalia Kryvinska ◽  
Marian Seliuchenko ◽  
Halyna Beshley ◽  
Elhadi M. Shakshuki ◽  
...  

This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT controller. A method for allocating uplink and downlink resources of the LTE/NB-IoT hybrid technology is applied to ensure the Quality of Service (QoS) from end-to-end. This method considers scheduling traffic/resources on the NB-IoT controller, which allows eNodeB planning to remain unchanged. This paper also proposes a prioritization approach within the IoT traffic to provide End-to-End (E2E) QoS in the integrated LTE/NB-IoT network. Further, we develop “smart queue” management algorithms for the IoT traffic prioritization. To demonstrate the feasibility of our approach, we performed a number of experiments using simulations. We concluded that our proposed approach ensures high end-to-end QoS of the real-time traffic by reducing the average end-to-end transmission delay.


2007 ◽  
Vol 35 (1-2) ◽  
pp. 21-42 ◽  
Author(s):  
Xinping Guan ◽  
Bo Yang ◽  
Bin Zhao ◽  
Gang Feng ◽  
Cailian Chen

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 619
Author(s):  
Dariusz Marek ◽  
Adam Domański ◽  
Joanna Domańska ◽  
Jakub Szyguła ◽  
Tadeusz Czachórski ◽  
...  

In this article, a way to employ the diffusion approximation to model interplay between TCP and UDP flows is presented. In order to control traffic congestion, an environment of IP routers applying AQM (Active Queue Management) algorithms has been introduced. Furthermore, the impact of the fractional controller PIγ and its parameters on the transport protocols is investigated. The controller has been elaborated in accordance with the control theory. The TCP and UDP flows are transmitted simultaneously and are mutually independent. Only the TCP is controlled by the AQM algorithm. Our diffusion model allows a single TCP or UDP flow to start or end at any time, which distinguishes it from those previously described in the literature.


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