Name
Abstract | ||
|---|---|---|
Empirical studies on link blacklisting show that the delivery rate is sensitive to the calibration of the blacklisting threshold. If the calibration is too restrictive (the threshold is too high), all neighbors get blacklisted. On the other hand, if the calibration is too loose (the threshold is too low), unreliable links get selected. This paper investigates blacklisting analytically. We derive a model that accounts for the joint effect of the wireless channel (signal strength variance and coherence time) and the network (node density). The model, validated empirically with mote-class hardware, shows that blacklisting does not help if the wireless channel is stable or if the network is relatively sparse. In fact, blacklisting is most beneficial when the network is relatively dense and the channel is unstable with long coherence times. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-28169-3_10 | EWSN |
Keywords | Field | DocType |
coherence time,link selection,wireless channel,wireless sensor network,optimal blacklisting threshold,blacklisting threshold,empirical study,joint effect,long coherence time,blacklisting analytically,link blacklisting show,delivery rate,mote-class hardware | Wireless,Computer science,Computer network,Communication channel,Real-time computing,Coherence (physics),Blacklisting,Signal strength,Wireless sensor network,Calibration,Coherence time | Conference |
Citations | PageRank | References |
2 | 0.40 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Flavio Fabbri | 1 | 50 | 5.45 |
| Marco Zuniga | 2 | 867 | 62.79 |
| Daniele Puccinelli | 3 | 233 | 19.40 |
| Pedro Jose Marron | 4 | 112 | 12.09 |