Network topology optimization tool (Ntot)

Author

Hamandishe, Farai.

Title

Network topology optimization tool (Ntot)

Abstract

Modern network infrastructures demand efficient and adaptable topologies to optimize performance, minimize latency, and ensure reliability. Traditional manual approaches to network topology optimization often fall short, leading to inefficiencies and suboptimal configurations. This research project addresses this challenge by developing a web-based Network Topology Optimization Tool (NTOT) designed to automate the process of analyzing network layouts and providing data-driven recommendations for improvement. The NTOT leverages Dijkstra's algorithm for shortest path calculations, a core component for identifying potential bottlenecks and optimizing network performance. The tool also incorporates centrality metrics, such as degree centrality and betweenness centrality, to provide network administrators with a comprehensive understanding of network structure and potential vulnerabilities. The development process involved a thorough requirement gathering phase, encompassing both functional and non-functional requirements. A modular system architecture was designed, integrating frontend functionalities using React.js, backend operations using Node.js, and data management using MongoDB. Rigorous testing was conducted using simulated network scenarios, encompassing various network sizes and topologies, to evaluate the tool's performance and validate the accuracy of the optimization recommendations. The research findings demonstrate the NTOT's effectiveness in achieving significant improvements in network performance, including notable reductions in path lengths, latency, and enhanced bandwidth utilization. The tool's efficient processing times and minimal resource utilization highlight its suitability for deployment in real-world network management scenarios. The project concludes by discussing the NTOT's potential for broader application in enterprise and cloud environments while acknowledging limitations and outlining areas for future development, including the integration of real-world network data, support for dynamic network changes, and the implementation of additional optimization algorithms. This research project represents a significant step towards streamlining network management and enhancing network performance in today's complex and dynamic network environments.

Date

June 2024

Publisher

BUSE

Keywords

Network infrastructures,

Network Topology Optimization Tool (NTOT),

Data management using MongoDB.

Supervisor

Mr. Musariwa,