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

**Authors:** Ankur Jain, Arohi Gupta, Ashutosh Gupta, Dewang Gedia, Leidy Pérez, Levi Perigo, Rahil Gandotra, Sanjay Murthy  
**arXiv:** [1904.10449](https://arxiv.org/abs/1904.10449)  
**Date:** 2019-04-23  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/1904.10449v1/

## Key points

- Existing research focuses on developing an intelligent system using big data telemetry analysis in PNDA for comprehensive trend-based networking decisions
- Goal is to analyze network data accurately and provide automated actions based on observed trends
- Scalable system developed for benchmarking the network and setting expected behavior for comparison and trend analysis
- Results include a GUI implemented through a web application for easy management of subsystems
- Proof of concept for actioning trend analysis results in traditional networks and SDN for dynamic and automated load balancing
- Leveraging big data telemetry analysis allows organizations to make more informed networking decisions and optimize network services
- Study demonstrates the potential of trend-based analytics in network management and benefits of incorporating big data telemetry analysis into existing systems.

## Summary

The existing research focuses on the development of an intelligent system that leverages big data telemetry analysis in the Platform for Network Data Analytics (PNDA) to enable comprehensive trend-based networking decisions. The goal is to accurately analyze network data and provide automated actions based on observed trends, which can minimize downtime and improve network performance. To address this challenge, the researchers have developed a scalable system capable of effectively benchmarking the network and setting expected behavior for comparison and trend analysis. The results include a graphical user interface (GUI) implemented through a web application, allowing effortless management of all subsystems. Furthermore, this research provides a proof of concept for how trend analysis results are actioned in both traditional networks and software-defined networks (SDN) to achieve dynamic and automated load balancing. By leveraging big data telemetry analysis, organizations can make more informed networking decisions and optimize their network services. Overall, this study demonstrates the potential of using trend-based analytics in network management and highlights the benefits of incorporating big data telemetry analysis into existing systems.