Work place: Ahmadu Bello University/Department of Electrical and Computer Engineering, Zaria, 234, Nigeria
Research Interests: Engineering, Computational Engineering, Computational Science and Engineering
Abdoulie Momodou Sunkary Tekanyi obtained his B.Eng. (Hons) degree in Electrical Engineering from the University of Sierra-Lone, Freetown in 1990, M.Sc Degree in Computer Networks from the Middlesex University, London in 2001, and PhD terminal degree in Electrical Engineering from Ahmadu Bello University, Zaria 2014. His PhD research thesis is Telecommunication Engineering based and centred on WLAN bandwidth improvement. His research interest is focused on Telecommunication Engineering, with emphasis on finding out problems of wireless and WLAN networks and their resolutions. In other words, finding out factors affecting efficient bandwidth utilization, channel congestion, traffic delay, and worst of all traffic loss of these networks. He is also interested in Computer Engineering work, particularly computer network security research area. He has more than 47 National and international publications from reputable journals and conferences. He is a member of Nigerian Society of Engineers (MNSE) and Member of International Research Development Institute (MIRDI).
DOI: https://doi.org/10.5815/ijigsp.2017.11.03, Pub. Date: 8 Nov. 2017
In this paper, an Adaptive Dynamic Scheduling Algorithm (ADSA) based on Artificial Bee Colony (ABC) was developed for vehicular traffic control. The developed model optimally scheduled green light timing in accordance with traffic condition in order to minimize the Average Waiting Time (AWT) at the cross intersection. A MATLAB based Graphic User Interface (GUI) traffic control simulator was developed. In order to demonstrate the effectiveness of the developed ADSA this paper was validated with the existing work in the literature. The result obtained for the AWT of the developed ADSA had a performance of 76.67%. While for vehicular queues cleared at the intersection the developed ADSA had a performance of 53.33%. The results clearly expressed that the developed ADSA method has been successful in minimizing the Average Waiting Time and vehicular queues at the intersection.[...] Read more.
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