The focus of this chapter shifts to application development based on the background elaborated in the previous chapters. First, a thorough system model will be presented. The architecture that encompasses the client–server interactions is detailed along with the functions and message of each block. In short, the browser extension coupled with the backend—i.e., Node.js—is built using a combination of HTML, CSS, and JavaScript to represent the client. With duplex communication between the client and the Node.js server, network traffic parameters are obtained from the network interface of the device before being subjected to prediction and classification ML techniques. As a result, parameters such as latency, jitter, and upload and download rates can be forecast in real time using a combination of the prediction time and window size variables set by the end user. This also applies for classification purposes where the real-time activity of the device is determined within a matter of seconds. Through thorough testing and deployment of the application in different networking scenarios, a functioning, reliable, and lightweight NTMA application is built.
NTMA Application with JavaScript
Machine Learning For Network Traffic and Video Quality Analysis ; Chapter : 5 ; 175-249
2024-06-20
75 pages
Article/Chapter (Book)
Electronic Resource
English
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