Name
Abstract | ||
|---|---|---|
It is widely assumed that certain network characteristics cause end-user irritation with network performance. These assumptions then drive the selection of quality of service parameters or the goals of adaptive systems. We have developed a methodology and toolchain, SoylentLogger, that employs user studies to empirically investigate such assumptions. SoylentLogger collects client-centric network measurement data that is labeled by the end-user as being associated with irritation at perceived network performance (or not). The data collection and labeling occurs in real-time as the user normally uses the network. We conducted a study that tracked 32 ordinary users over a period of 3 weeks and then used that data to test common assumptions about network sources of user irritation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2018602.2018613 | W-MUST@SIGCOMM |
Keywords | DocType | Citations |
data collection,ordinary user,certain network characteristic,network source,network problem,end-user irritation,end-user perception,client-centric network measurement data,user study,user irritation,network performance,adaptive system,quality of service,real time | Conference | 5 |
PageRank | References | Authors |
0.59 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. Scott Miller | 1 | 46 | 4.45 |
| Amit Mondal | 2 | 35 | 4.40 |
| Rahul Potharaju | 3 | 549 | 27.66 |
| Peter A. Dinda | 4 | 1493 | 126.40 |
| Aleksandar Kuzmanovic | 5 | 960 | 71.99 |