International Conference on Computer and Knowledge Engineering

Home / 13th International Conference on Computer and Knowledge Engineering

Community-Based QoE Enhancement for User-Generated Content Live Streaming

Authors :

Reza Saeedinia¹ S.Omid Fatemi² Daniele Lorenzi³ Farzad Tashtarian⁴ Christian Timmerer⁵

1- ECE Department University of Tehran 2- ECE Department University of Tehran 3- Alpen-Adria-Universitat at Klagenfurt, Austria 4- Alpen-Adria-Universitat at Klagenfurt, Austria 5- Alpen-Adria-Universitat at Klagenfurt, Austria

Keywords :

User-generated content،live streaming،community detection algorithm،quality of experience،resource allocation

Abstract :

Live user-generated content (UGC) has increased significantly in video streaming applications. Improving the quality of experience (QoE) for users is a crucial consideration in UGC live streaming, where a user can be both a subscriber and a streamer. Resource allocation is an NP-complete task in UGC live streaming due to many subscribers and streamers with varying requests, bandwidth limitations, and network constraints. In this paper, to decrease the execution time of the resource allocation algorithm, we first process streamers’ and subscribers’ requests and then aggregate them into a limited number of groups based on their preferences. Second, we perform resource allocation for these groups that we call communities. We formulate the resource allocation problem for communities into an optimization problem. With an efficient aggregation of subscribers and streamers at the core of the proposed architecture, the computational complexity of the optimization problem is reduced, consequently improving QoE. This improvement occurs because of the prompt reaction to the bandwidth fluctuations and, subsequently, appropriate resource allocation by the proposed model. We conduct experiments in various scenarios. The results show an average of 41% improvement in execution time. To evaluate the impact of bandwidth fluctuations on the proposed algorithm, we employ two network traces: AmazonFCC and NYUBUS. The results show 4%, and 28% QoE improvement in a scenario with 5 streamers over the AmazonFCC and the NYUBUS network traces, respectively.

Papers List

List of archived papers

Generating Hand-Written Symbols With Trajectory Planning Using A Robotic Arm

Arya Parvizi - Armin Salimi-Badr

DPRNN-FORMER: AN EFFICIENT WAY TO DEAL WITH BLIND SOURCE SEPARATION

Ramin Ghorbani - Sajad Haghzad Klidbary

A Comprehensive Approach to SMS Spam Filtering Integrating Embedded and Statistical Features

Shaghayegh Hosseinpour - Mohammad Reza Keyvanpour

A Framework for Automated Cardiovascular Magnetic Resonance Image Quality Scoring based on EuroCMR Registry Criteria

Shahabedin Nabavi - Mohsen Ebrahimi Moghaddam - Ahmad Ali Abin - Alejandro Frangi

Span-prediction of Unknown Values for Long-sequence Dialogue State Tracking

Marzieh Naghdi Dorabati - Reza Ramezani - Mohammad Ali Nematbakhsh

A Comprehensive Dataset of Real-scene Images for Text Detection and Recognition in Persian

Iman Souzanchi - Ramin Rahimi - Mohammad Ali Majidi Anvari - Atefeh Baniasadi - Ashkan Sadeghi - Mohammad Reza Mohammadi

Intracranial Hemorrhage Classification using CBAM Attention Module and Convolutional Neural Networks

Parnian Rahimi - Marjan Naderan - Amir Jamshidnezhad - Shahram Rafie

Compressing Deep Neural Networks Using Explainable AI

Kimia Soroush - Mohsen Raji - Behnam Ghavami

Using Deep Learning for Classification of Lung Cancer on CT Images in Ardabil Province

Mohammad Ali Javadzadeh Barzaki - Jafar Abdollahi - Mohammad Negaresh - Maryam Salimi - Hadi Zolfeghari - Mohsen Mohammadi - Asma Salmani - Rona Jannati - Firouz Amani

Age Estimation Based on Facial Images Using Hybrid Features and Particle Swarm Optimization

NILOUFAR MEHRABI - SAYED PEDRAM HAERI BOROUJENI