Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
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Abstract
In this study, current network architecture and characteristics of the campus network at the University of Kufa (UoK) is presented and survey. The research methodology includes preliminary study, data collection and analysis, modeling, proposing and evaluation phase. A survey questionnaire is conducted to evaluate the current network performance from the user’s perspective and administrators for different colleges. Data are collected from 186 respondents that included 178 employees and 8 admins through online and paper surveys. Survey results have shown that most users are not satisfied with the existing network performance regarding several network services such as availability, Quality of Service (QoS). Additionally, the survey is validated by three experts through a structured interview. Most of the feedback from the experts match the results of the questionnaire. Thus, after identified several factors that could be influenced, we proposed a number of criteria to enhance the performance of the current network such as fault-tolerance, scalability, Quality of Service (QoS) and security. To achieve the proposed criteria, packet tracer software is used to design and simulate the new network architecture. The proposed campus network design is capable of delivering a service with 24/7 availability, ability to accommodate the increased number of users in future, the ability of packet prioritizing and improved security. Finally, a structured interview is conducted to validate the proposed design by five experts. Most of the feedback of the experts' match the results of the research that led the proposed switched campus network is acceptance.
How to cite this article:
Mohammed Falih Kadhim, Nabeel Salih Ali and Salam Al-Khammasi. Multi-Phase Methodology for Proposing a High Performance Switched
Campus Network: University of Kufa Case Study.
DOI: https://doi.org/10.36478/jeasci.2018.6700.6707
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.6700.6707