Name
Abstract | ||
|---|---|---|
Preemption and adaptation are two common techniques for controlling inelastic traffic such as streaming media. Adaptation policies dynamically increase or decrease the transmission rate of the stream in response to the presence or absence of network congestion. On the other hand, preemption policies select streams to be removed from the congested route. The removed streams may be rerouted through less favorable paths in the network. Adaptation causes a "virtual increase in network capacity" at the cost of reducing the client perceived stream quality (since rate reduction is achieved through lossy compression). Preemption permits improved blocking probabilities and traffic alignment on shortest paths for high priority traffic at the expense of performance degradation for low priority traffic. In this paper, we demonstrate the aforementioned performance trade-offs and the increased efficacy of control achievable through the combined use of preemption and adaptation policies. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICC.2006.254784 | Communications, 2006. ICC '06. IEEE International Conference |
Keywords | Field | DocType |
degradation,lossy compression,next generation networking,bandwidth,shortest path,network topology,encoding,network congestion | Transmission rate,Next-generation network,Preemption,Lossy compression,Computer science,Computer network,Network topology,Real-time computing,Bandwidth (signal processing),Network congestion,Encoding (memory) | Conference |
Volume | ISSN | ISBN |
2 | 8164-9547 E-ISBN : 1-4244-0355-3 | 1-4244-0355-3 |
Citations | PageRank | References |
1 | 0.39 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven Weber | 1 | 724 | 53.55 |
| Jaudelice Cavalcante de Oliveira | 2 | 186 | 16.85 |
| Sukrit Dasgupta | 3 | 28 | 2.32 |
| Bryan Willman | 4 | 77 | 14.64 |
| Zhen Zhao | 5 | 1 | 0.39 |
| de Oliveira, J.C. | 6 | 10 | 1.58 |