Trend-Based Networking Driven by Big Data Telemetry for Sdn and Traditional Networks

Organizations face a challenge of accurately analyzing network data and providing automated actionbased on the observed trend. This trend-based analytics is beneficial to minimize the downtime andimprove the performance of the network services, but organizations use different network managementtools to understand and visualize the network traffic with limited abilities to dynamically optimize thenetwork. This research focuses on the development of an intelligent system that leverages big datatelemetry analysis in Platform for Network Data Analytics (PNDA) to enable comprehensive trendbased networking decisions. The results include a graphical user interface (GUI) done via a webapplication for effortless management of all subsystems, and the system and application developed inthis research demonstrate the true potential for a scalable system capable of effectively benchmarkingthe network to set the expected behavior for comparison and trend analysis. Moreover, this researchprovides a proof of concept of how trend analysis results are actioned in both a traditional network anda software-defined network (SDN) to achieve dynamic, automated load balancing.