at Google ScholarTitle data
Schönfeld, Mirco ; Werner, Martin:
Node Wake-Up via OVSF-Coded Bloom Filters in Wireless Sensor Networks.
In: Sherif, Mostafa Hashem ; Mellouk, Abdelhamid ; Li, Jun ; Bellavista, Paolo
(ed.):
Ad Hoc Networks : 5th International ICST Conference, ADHOCNETS 2013 ; Revised Selected Papers. -
Cham
: Springer
,
2014
. - pp. 119-134
. - (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
; 129
)
ISBN 978-3-319-04104-9
DOI: https://doi.org/10.1007/978-3-319-04105-6_8
Abstract in another language
Interest dissemination in constrained environments such as wireless sensor networks utilizes Bloom filters commonly. A Bloom filter is a probabilistic data structure of fixed length, which can be used to encode the set of sensor nodes to be awake. In this way an application can disseminate interest in specific sensor nodes by broadcasting the Bloom filter throughout the complete wireless sensor network. The probabilistic nature of a Bloom filter induces false positives, that is some sensor nodes will be awake without the application having interest in their sensor values. As the interest is often depending on location such as in adaptive sampling applications, we present a novel method to encode both interest and possible location of information into one probabilistic data structure simultaneously. While our algorithm is able to encode any kind of tree-structured information into a fixed length bit array we exemplify its use through a wireless sensor network. In comparison to traditional Bloom encoding techniques we are able to reduce the overall number of false positives and furthermore reduce the average distance of false positives from the next true positive of the same interest. In our example this helps to reduce the overall energy consumption of the sensor network by only requesting sensor nodes that are likely to store the requested information.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| Institutions of the University: | Faculties > Faculty of Languages and Literature Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld Faculties |
| Result of work at the UBT: | No |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 18 Nov 2021 13:54 |
| Last Modified: | 18 Nov 2021 13:54 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/67898 |