International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 07 | July 2024
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p-ISSN: 2395-0072
Capturing and Mitigating Network Delay and Packet Loss Using Artificial Intelligence Zeeshan Ahmed Mohammed1, Ubaid Ul Mannan Mohammed2, Muneeruddin Mohammed3, Abdul Junaid Mohammed4 1,2,3,4 University of the Cumberlands , Williamsburg, KY. -----------------------------------------------------------------------------***-------------------------------------------------------------------Abstract
Network performance is crucial for the seamless operation of internet services and applications. Key performance indicators such as network delay (latency) and packet loss significantly affect user experience and service quality. Traditional monitoring techniques, while effective in diagnosing issues, often lack predictive capabilities. This paper explores the application of artificial intelligence (AI) in capturing and mitigating network delay and packet loss. By leveraging machine learning and deep learning models, AI can predict and address network performance issues in real-time, enhancing reliability and efficiency. This research delves into the background and current state of network performance monitoring, reviews existing literature on AI applications in this domain, discusses the challenges in implementing AI-driven solutions, and provides recommendations for future research and development. Keywords: Network delay, Packet loss, AI, Machine learning, Deep learning, Network performance, Predictive analytics. I.
Introduction
In the digital age, network performance is pivotal for both consumer and enterprise applications. Whether it's video conferencing, online gaming, or cloud computing, the reliability and speed of network connections determine user satisfaction and operational efficiency. Two critical metrics in evaluating network performance are network delay (latency) and packet loss. Latency is the time it takes for a data packet to travel from its source to its destination, while packet loss refers to the failure of data packets to reach their intended destination. High latency and packet loss can severely degrade the quality of service, leading to interruptions, slow data transfers, and overall poor user experience. Traditional network monitoring tools, such as Wireshark and NetFlow, have been instrumental in diagnosing network issues. However, these tools often operate reactively, identifying problems only after they have impacted network performance. Proactive and predictive solutions are desperately needed given the size and complexity of today's networks. Artificial intelligence (AI) is useful in this situation. Through the use of artificial intelligence (AI), specifically machine learning (ML) and deep learning (DL) models, network performance problems can be predicted and addressed before they have an impact on end users. This paper examines the application of AI in capturing and mitigating network delay and packet loss. It explores the background and current state of network performance monitoring, reviews existing literature on AI applications in this domain, discusses the challenges in implementing AI-driven solutions, and provides recommendations for future research and development.
II.
Background Study
Network delay and packet loss are critical performance metrics that affect the quality of service (QoS) in networked applications. Understanding their causes and effects is essential for developing effective mitigation strategies 2.1. Network Delay The time it takes for a data packet to move from its source to its destination across a network is known as network delay, or latency. The performance and usability of many applications, particularly those that demand real-time data transmission like voice over IP (VoIP), online gaming, and video conferencing, can be severely impacted by this delay. (Cisco, 2020).
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