Mr. Amaresan venkatesan

AI in Computer Networks and fault analysis

Abstract:

In today’s hyper-connected world, network reliability is crucial for the smooth functioning of businesses, governments, and individuals. As networks grow more complex and mission-critical, the challenges of diagnosing faults and ensuring uptime have become increasingly difficult. Traditional methods of fault detection are often reactive, slow, and labor-intensive, leading to costly downtimes and degraded performance. Artificial Intelligence (AI), specifically machine learning (ML) and deep learning (DL), is transforming the landscape of network fault diagnosis and enhancing overall network reliability. By enabling proactive fault detection, real-time root cause analysis, and automated remediation, AI empowers networks to identify and resolve issues before they cause significant disruptions. AI-driven tools can also optimize network resource allocation, self-heal from faults, and dynamically adapt to changing conditions, improving performance and reducing downtime. This speech will explore how AI is revolutionizing network fault diagnosis, highlighting its key applications in anomaly detection, predictive maintenance, and automated problem resolution. Additionally, the speech will cover how AI is contributing to the creation of self-healing, highly reliable networks that can proactively prevent failures and maintain continuous service. Finally, we will examine real-world case studies that demonstrate the impact of AI in network reliability, along with challenges and considerations for implementing AI-driven solutions. Attendees will leave with a clear understanding of how AI can dramatically improve fault diagnosis, reduce downtime, and increase the overall reliability of modern networks.