Ibraheem Kasim Ibraheem

Work place: Department of Electrical Engineering, Baghdad University, Baghdad, Iraq

E-mail: ibraheemki@coeng.uobaghdad.edu.iq

Website:

Research Interests: Computer Architecture and Organization, Process Control System, Error Control, Data Structures and Algorithms, Control Theory

Biography

Ibraheem K. Ibraheem was born on August 23, 1976, in Baghdad, Iraq. He received the B.S. degree in electrical engineering from the University of Baghdad, Baghdad, Iraq in 1998 and M.Sc. & Ph.D. degrees in Computer & Control Engineering from the same university and department, in 2001 and 2007, respectively. His research interests include Optimization in wireless networks, evolutionary and dynamic Optimizations, signal processing, nonlinear control and intelligent control applications.

Author Articles
A Multi QoS Genetic-based Adaptive Routing in Wireless Mesh Networks with Pareto Solutions

By Ibraheem Kasim Ibraheem Alyaa Abdul-Hussain Al-Hussainy

DOI: https://doi.org/10.5815/ijcnis.2018.09.01, Pub. Date: 8 Sep. 0218

Wireless Mesh Networks(WMN) is an active research topic for wireless networks designers and researchers. Routing has been studied in the last two decades in the field of optimization due to various applications in WMN. In this paper, Adaptive Genetic Algorithm (AGA) for identifying the shortest path in WMN satisfying multi- QoS measure is introduced. The proposed algorithm is adaptive in the sense that it uses various selection methods during the reproduction process and the one with the best multi- QoS measure is adopted in that generation. The multi-objective QoS measure defined as the combination of the minimum number of hops, minimum delay, and maximum bandwidth. The multi-objective optimization has been formulated and solved using weighted sum approach with Pareto optimal solution techniques. The simulation experiments have been carried out in MATLAB environment with a wireless network modeled as weighted graph of fifty nodes and node coverage equals to 200 meter, and the outcomes demonstrated that the proposed AGA performs well and finds the shortest route of the WMN proficiently, rapidly, and adapts to the dynamic nature of the wireless network and satisfying all of the constraints and objective measures imposed on the networks.

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