Name
Title | ||
|---|---|---|
Network Fortune Cookie: Using Network Measurements to Predict Video Streaming Performance and QoE. |
Abstract | ||
|---|---|---|
Due to the fact that video streaming is the current "killer" application and for competitiveness, telecommunication service providers need to be able to answer a fundamental question: to which extent is the available network infrastructure able to successfully provide users with a satisfactory experience when running video streaming applications? Answering this question is far from trivial because existing techniques are neither scalable nor accurate enough. To address this issue, we propose a model to predict video streaming quality based on the observation of performance indicators of the underlying IP network. To accomplish this objective, the proposed model - created using LTE networks as case study - leverages low network consumption active measurements and machine learning techniques. Obtained results show that the proposed solution produces accurate estimates (average error of less than 10%) while keeping intrusiveness around twenty times lower than traditional techniques. |
Year | Venue | Field |
|---|---|---|
2016 | IEEE Global Communications Conference | Decision tree,Performance indicator,Computer science,Internet protocol suite,Quality of service,Computer network,Intrusiveness,Real-time computing,Throughput,Telecommunications service,Scalability |
DocType | ISSN | Citations |
Conference | 2334-0983 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Iraja Tavares da Costa Filho | 1 | 0 | 0.34 |
| William Lautenschlager | 2 | 0 | 1.01 |
| Nicolas Kagami | 3 | 1 | 1.03 |
| Valter Roesler | 4 | 36 | 11.96 |
| Luciano Paschoal Gaspary | 5 | 433 | 52.11 |