Swarm intelligence based robust active queue management design for congestion control in computer network

مقدم أطروحة جامعية

Khalid, Karam Samir

مشرف أطروحة جامعية

Ali, Hazim Ibrahim

الجامعة

الجامعة التكنولوجية

الكلية

-

القسم الأكاديمي

قسم هندسة السيطرة و النظم

دولة الجامعة

العراق

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2013

الملخص الإنجليزي

The congestion refers to a loss of network performance when a network is heavily loaded which leads to data loss and large delays.

In this work, three robust control algorithms are proposed to work as an Active Queue Management (AQM) which is an effective mechanism for congestion control problem.

These algorithms are; conventional H∞ controller, robust Particle Swarm Optimization based PID (PSOPID) controller and robust Ant Colony Optimization based PID (ACOPID) controller.

The design procedure of conventional H∞ method is complex and difficult to fine tuning the weighting functions in order to achieve the robust performance and robust stability.

Furthermore, the order of the resulting conventional H∞ controller is high, therefore; the Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) methods are used to tune the PID controller and the weighting functions parameters.

The parameters of the PID controller in the two types of controllers are tuned subject to H∞ constraints to achieve the required robustness of the network.

The robust PSOPID and ACOPID controllers can achieve desirable time response specifications with simple design procedure and low order controller in comparison to the conventional H∞ controller.

Low and wide ranges of system parameters change are used to show the robustness of the proposed controllers.

The ability of the proposed controllers to meet the specified performance is demonstrated using MATLAB 7.11.

On the other hand, to verify the effectiveness of the proposed controllers, a modification by adding the proposed control algorithms to the Ns2 (network simulator) function to perform the nonlinear simulation is done.

Finally, it is shown that the proposed robust ACOPID controller can achieve rise time = 0.408 sec., settling time =0.77 sec., mean =195.6 and standard deviation = 33.09, which are more desirable performance specifications compared to those obtained by the proposed robust PSOPID controller and the controllers that have been designed in previous works.

التخصصات الرئيسية

العلوم الهندسية والتكنولوجية (متداخلة التخصصات)

الموضوعات

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Khalid, Karam Samir. (2013). Swarm intelligence based robust active queue management design for congestion control in computer network. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-418059

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Khalid, Karam Samir. Swarm intelligence based robust active queue management design for congestion control in computer network. (Master's theses Theses and Dissertations Master). University of Technology. (2013).
https://search.emarefa.net/detail/BIM-418059

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Khalid, Karam Samir. (2013). Swarm intelligence based robust active queue management design for congestion control in computer network. (Master's theses Theses and Dissertations Master). University of Technology, Iraq
https://search.emarefa.net/detail/BIM-418059

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-418059