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.
|Title of host publication||Wireless Sensor Networks - 9th European Conference, EWSN 2012, Proceedings|
|Number of pages||16|
|Publication status||Published - 2012|
|Event||9th European Conference on Wireless Sensor Networks, EWSN 2012 - Trento, Italy|
Duration: 15 Feb 2011 → 17 Feb 2011
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||9th European Conference on Wireless Sensor Networks, EWSN 2012|
|Period||15/02/11 → 17/02/11|
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