Name
Abstract | ||
|---|---|---|
P2P live streaming system is one of the most popular Internet applications which develop rapidly in the past decade. However, some common problems, such as long startup delay and unsmooth playback, seriously restrict user’s experience on live streaming. In this paper, we propose a novel but simple scheme, namely guarantee mechanism of contingency resource (GMCR), which can improve the quality of service (QoS) of live streaming by deploying a contingency server to provide contingency service for those chunks whose playback deadlines are urgent. Then we establish a queuing model to analyze the quantitative relation between the amount of contingency server resources and the level of user’s QoS. Finally, we simulate our scheme in a P2P live streaming simulation platform, and obtain the optimal value of some critical parameters. The results of theoretical analysis and simulation experiment present the feasibility and validity of GMCR scheme. |
Year | Venue | Field |
|---|---|---|
2015 | Informatica (Slovenia) | Computer science,Computer network,Quality of service,Real-time computing,Queueing theory,Artificial intelligence,Live streaming,Contingency,Machine learning,restrict,The Internet |
DocType | Volume | Issue |
Journal | 39 | 4 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guomin Zhang | 1 | 123 | 15.78 |
| Chao Hu | 2 | 28 | 7.42 |
| Na Wang | 3 | 7 | 11.10 |
| Xiang-Lin Wei | 4 | 117 | 26.16 |
| Changyou Xing | 5 | 47 | 10.55 |