Novel Active Queue Management Scheme for Routers in Wireless Networks

Okokpujie, Kennedy; Chukwu, Emmanuel C.; Noma‐Osaghae, Etinosa; Okokpujie, Imhade P.

doi:10.15866/irecap.v8i1.13408

Cited by 18 publications

(9 citation statements)

References 14 publications

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“…More recently, the authors in [12] developed an hybrid model which uses PPC technique to solve congestion problems in TCP/AQM compliant networks. It also combines backstepping and H∞ control mechanisms [13]. Their simulation results, like [14], show the robustness of the hybrid algorithm and the adaptive nature was also confirmed by varying the network components but did not also consider the effect of varying link capacity and propagation delay [15][16][17][18][19].…”

mentioning

confidence: 99%

Comparative analysis of the performance of various active queue management techniques to varying wireless network conditions

Okokpujie

Chukwu

Shobayo

et al. 2019

IJECE

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This paper demonstrates the robustness of active queue management techniques to varying load, link capacity and propagation delay in a wireless environment. The performances of four standard controllers used in Transmission Control Protocol/Active Queue Management (TCP/AQM) systems were compared. The active queue management controllers were the Fixed-Parameter Proportional Integral (PI), Random Early Detection (RED), Self-Tuning Regulator (STR) and the Model Predictive Control (MPC). The robustness of the congestion control algorithm of each technique was documented by simulating the varying conditions using MATLAB® and Simulink® software. From the results obtained, the MPC controller gives the best result in terms of response time and controllability in a wireless network with varying link capacity and propagation delay. Thus, the MPC controller is the best bet when adaptive algorithms are to be employed in a wireless network environment. The MPC controller can also be recommended for heterogeneous networks where the network load cannot be estimated.

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mentioning

confidence: 99%

Comparative analysis of the performance of various active queue management techniques to varying wireless network conditions

Okokpujie

Chukwu

Shobayo

et al. 2019

IJECE

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“…The analysis of known solutions [4,5,[10][11][12][13][14][15][16][17][18][19][20][21][22] has shown that the results of the solution of the Congestion Management problem are not related to the results of the Resource Allocation and Congestion Avoidance tasks. That is why, in order to reduce the computational complexity of the calculations of the optimization problems, their distributed solution was proposed within the framework of the two-step method ( fig.…”

Section: Discussionmentioning

confidence: 99%

“…The disadvantage of this work is the lack of differentiation and fairness in serving traffic flows with different QoS requirements. [15,16,[20][21][22] presents mathematical models and queuing control methods that combine both queuing planning methods and active queuing methods. The main disadvantage of these models and methods is the high dimension of optimization tasks, which leads to an increase in the computational complexity of obtaining the desired solutions and complication of their subsequent algorithmic-software implementation.…”

Section: Introductionmentioning

confidence: 99%

Method of Scheduling and Active Queues Management on Routers Interfaces of Telecommunication Networks

Lebedenko

2019

Innovative Technologies and Scientific Solutions for Industries

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The subject matter of the article is the method of scheduling and active queues management on routers interfaces of telecommunication networks. The goal of the work is to develop and improve the method related to the optimization of queues management processes on routers interfaces of telecommunication networks and aimed at improving the indicators of the quality of service. The article solves optimization problems of Congestion Management, Resource Allocation and Congestion Avoidance on routers interfaces of telecommunication networks in the framework of the two-stage calculation method. Research methods are based on the results of analytical calculations obtained in the course of using the Optimization Toolbox package of the Mat lab environment. Wherein in the course of improving the queue management method on routers interfaces of telecommunication networks, a mathematical programming apparatus was used, containing linear programming functions. The following results were obtainedthe improved method of scheduling and active queues management on routers interfaces of telecommunication networks with the coordinated, sequential and two-stage solution of such interface problems as Congestion Management, Resource Allocation, and Congestion Avoidance. Conclusions: using the proposed method of scheduling and active queue management had made to achieve an agreed solution to Congestion Management, Resource Allocation, and Congestion Avoidance problems. In the course of solving the optimization problem of Congestion Management, which was conditionally related to the first stage of calculations, it was possible to achieve optimal aggregation and allocation of packet flows over queues formed on the router interface based on the commensurability of their classes. In the course of solving the optimization problems of resource allocation, and congestion avoidance, which were conditionally related to the second stage of calculations, it was possible to achieve an optimal bandwidth allocation of the router interface between the queues formed on it, and minimize possible denials of service.

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“…Comb and block pilot arrangements are the two types of pilot systems that are available for channel estimation techniques [15], [16]. The main difference between the comb and the block type arrangement is that the pilot tones are inserted into each OFDM symbol at periodic intervals of the subcarrier frequency in the comb type, while the pilots are inserted within the frequency subcarrier in the block type arrangement.…”

Section: Ii4 Pilot Arrangements In Channel Estimationmentioning

confidence: 99%

“…In this paper, channel estimation in a wireless communication system was simulated using MATLAB [24], [25]. For the simulation to be effective, a system with a transmitter, receiver and channel was implemented.…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of MIMO-OFDM Channel Estimation in Wireless Systems

Okoyeigbo

Okokpujie

Noma‐Osaghae

et al. 2018

IREMOS

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Determining the channel characteristics and how it affects transmitted signals is known as channel estimation. MIMO OFDM is a combination of MIMO and OFDM techniques. In this paper, comparative studies of MIMO, MISO and SISO channel estimation, using OFDM was performed. The block type and the comb type pilot arrangements were compared, and also various interpolation techniques were also compared to determine the optimum performance. The Bit Error Rate and MSE were employed as the performance metrics. This research was carried out by modeling and simulating the wireless communication system using MATLAB. It was discovered that the FFT interpolation has the best performance compared to other interpolation techniques. It was also shown that the MMSE outperformance the LS, but this is achieved at the cost of system complexity. An improvement in system performance was also observed with an increase in the number of antennas (i.e SISO, MISO and MIMO respectively), and also the OFDM helps combat interference and improves the bandwidth efficiency.

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Novel Active Queue Management Scheme for Routers in Wireless Networks

Cited by 18 publications

References 14 publications

Comparative analysis of the performance of various active queue management techniques to varying wireless network conditions

Comparative analysis of the performance of various active queue management techniques to varying wireless network conditions

Method of Scheduling and Active Queues Management on Routers Interfaces of Telecommunication Networks

Comparative Study of MIMO-OFDM Channel Estimation in Wireless Systems

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