Machine Learning-based Stable P2P IPTV Overlay  

作　　者：Muhammad Javid Iqbal Ihsan Ullah Muhammad Ali Atiq Ahmed Waheed Noor Abdul Basit 

机构地区：[1]Directorate of Information Technology,Sardar Bahadur Khan Women’s University,Quetta,Pakistan [2]Department of Computer Science and Information Technology,University of Balochistan,Quetta,Pakistan

出　　处：《Computers, Materials & Continua》2022年第6期5381-5397,共17页计算机、材料和连续体（英文）

摘　　要：Live video streaming is one of the newly emerged services over the Internet that has attracted immense interest of the service providers.Since Internet was not designed for such services during its inception,such a service poses some serious challenges including cost and scalability.Peer-to-Peer(P2P)Internet Protocol Television(IPTV)is an application-level distributed paradigm to offer live video contents.In terms of ease of deployment,it has emerged as a serious alternative to client server,Content Delivery Network(CDN)and IP multicast solutions.Nevertheless,P2P approach has struggled to provide the desired streaming quality due to a number of issues.Stability of peers in a network is one of themajor issues among these.Most of the existing approaches address this issue through older-stable principle.This paper first extensively investigates the older-stable principle to observe its validity in different scenarios.It is observed that the older-stable principle does not hold in several of them.Then,it utilizes machine learning approach to predict the stability of peers.This work evaluates the accuracy of severalmachine learning algorithms over the prediction of stability,where the Gradient Boosting Regressor(GBR)out-performs other algorithms.Finally,this work presents a proof-of-concept simulation to compare the effectiveness of older-stable rule and machine learning-based predictions for the stabilization of the overlay.The results indicate that machine learning-based stability estimation significantly improves the system.

关 键 词：P2P IPTV live video streaming user behavior overlay networks stable peers machine learning 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]