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Comparative analysis of different network designs, connections, and performance measurement using optimized network engineering tools (OPNET) modeler.

Date Issued
2024
Author(s)
Nzobokela, Kulonga
Abstract
The study conducted at the Technical and Vocational Teachers' College (TVTC) aimed to optimize its Local Area Networks (LANs) following a survey via a Google Forms questionnaire, which identified problem gaps. This led to stating a research problem statement and prompted a network redesign and upgrade. A comprehensive comparative analysis of various network designs, connections, and performance measurements was conducted using the Optimized Network Engineering Tool (OPNET) Modeler. The study aimed to discern factors influencing network performance and Quality of Service (QoS), with the goal of designing networks for optimal functionality and recommending superior configurations. Utilizing OPNET simulation software, scenarios were crafted to address connectivity challenges at TVTC, revealing significant bottlenecks across diverse network designs and connections. Higher link capacities demonstrated lower HTTP response times, while lower capacities struggled with simultaneous traffic, resulting in delays. First In, First Out (FIFO) exhibited the highest data traffic drop, whereas Weighted Fair Queuing (WFQ) showcased the lowest drop rate. LAN delay increased with user volume, and WFQ proved most effective for video traffic, while Priority Queuing (PQ) excelled in handling Voice Traffic. Building upon this analysis, recommendations are provided to enhance network performance and QoS. Prioritizing investments in high-bandwidth infrastructure and adopting efficient queuing mechanisms like WFQ are crucial. Regular assessment and adjustment of network configurations, along with the implementation of Quality of Service (QoS) strategies tailored for video and voice traffic, are essential for maintaining service quality. This study makes a substantial contribution to network engineering knowledge, benefiting IT professionals, organizations, and educational institutions by providing actionable insights and best practices. It promotes informed decision-making, encourages standardization across sectors, and lays the groundwork for future advancements in network optimization. By offering practical solutions to modern challenges, it advances our understanding of network dynamics and serves as a foundation for ongoing innovation and improvement in network engineering practices.
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