Work place: Salman Bin Abulaziz University, KSA
E-mail: s.soliman@sau.edu.sa
Website: https://scholar.google.com/citations?user=_WrgIbIAAAAJ&hl=en
Research Interests: Wireless Ad Hoc Network, Mobile Computing, Wireless Networks, Wireless Communication
Biography
Saied M. Abd El-atty received the B.S. and M.S. degrees from Menoufia University, Faculty of Electronic Engineering, in 1995 and 2001, all in Electronics & Communications Engineering respectively and PhD degree in Wireless Communication Networks from University of Aegean (UOA) at the Information and Communication Systems Engineering Department, Greece, Samos in 2008. He is a member of the faculty members in the department of Electronics and Electrical Communication at Faculty of Electronic Engineering, Menouf, Egypt. Currently, he is working as assistant professor in Salman Bin Abulaziz University, KSA. He is the head of computer science and information department in Science College. Dr. Saied’s current research interests include design, analysis, and optimization of wireless mobile communication networks and vehicular networks as well as cognitive radio systems. Majoring in Cross layer schemes, Handover, Radio Resource Management, Teletraffic, Vehicular Networks, Scheduling, small cell technology.
By Saied M. Abd El-atty Konstantinos Lizos
DOI: https://doi.org/10.5815/ijcnis.2014.04.01, Pub. Date: 8 Mar. 2014
Advanced heterogeneous vehicular network (AHVN) is a promising architecture for providing vehicular services in the next generation of vehicular networks. AHVN is an integrated architecture between vehicular ad hoc networks and existing cellular wireless networks. In this work, we propose a Multihop vehicular connectivity model in V2V system, which depends on the physical characteristics of the roadways and false hop initiation connectivity. Then, we determine the failure probability of vehicular connectivity in V2V system. Based on interoperability utility, we employ the failure connectivity probability as a handover criterion to communicate with V2R networks. Subsequently, we propose an efficient medium access control (MAC) method based on collaborative codes for resource management in AHVN. As a result, we determine the failure access probability by employing a Markov chain model. The analysis of the proposed MAC in terms of transmission capacity, delay and access failure probability is driven. The numerical and simulation results demonstrate the effectiveness of the proposed framework.
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