Conference Paper: Deterministic distributed data aggregation under the SINR model
| Title | Deterministic distributed data aggregation under the SINR model |
|---|---|
| Authors | Hobbs, N2 Wang, Y2 Hua, QS2 Yu, D1 Lau, FCM1 |
| Keywords | Data Aggregation Physical Carrier Sensing Sinr Interference Model |
| Issue Date | 2012 |
| Publisher | Springer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/ |
| Citation | Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2012, v. 7287 LNCS, p. 385-399 [How to Cite?] DOI: http://dx.doi.org/10.1007/978-3-642-29952-0_38 |
| Abstract | Given a set of nodes ν, where each node has some data value, the goal of data aggregation is to compute some aggregate function in the fewest timeslots possible. Aggregate functions compute the aggregated value from the data of all nodes; common examples include maximum or average. We assume the realistic physical (SINR) interference model and no knowledge of the network structure or the number of neighbors of any node; our model also uses physical carrier sensing. We present a distributed protocol to compute an aggregate function in O(D+Δlogn) timeslots, where D is the diameter of the network, Δ is the maximum number of neighbors within a given radius and n is the total number of nodes. Our protocol contributes an exponential improvement in running time compared to that in [18]. © 2012 Springer-Verlag. |
| ISSN | 0302-9743 2011 SCImago Journal Rankings: 0.034 |
| DOI | http://dx.doi.org/10.1007/978-3-642-29952-0_38 |
| References | References in Scopus |
| dc.contributor.author | Hobbs, N |
|---|---|
| dc.contributor.author | Wang, Y |
| dc.contributor.author | Hua, QS |
| dc.contributor.author | Yu, D |
| dc.contributor.author | Lau, FCM |
| dc.date.accessioned | 2012-06-26T06:32:48Z |
| dc.date.available | 2012-06-26T06:32:48Z |
| dc.date.issued | 2012 |
| dc.description.abstract | Given a set of nodes ν, where each node has some data value, the goal of data aggregation is to compute some aggregate function in the fewest timeslots possible. Aggregate functions compute the aggregated value from the data of all nodes; common examples include maximum or average. We assume the realistic physical (SINR) interference model and no knowledge of the network structure or the number of neighbors of any node; our model also uses physical carrier sensing. We present a distributed protocol to compute an aggregate function in O(D+Δlogn) timeslots, where D is the diameter of the network, Δ is the maximum number of neighbors within a given radius and n is the total number of nodes. Our protocol contributes an exponential improvement in running time compared to that in [18]. © 2012 Springer-Verlag. |
| dc.description.nature | Link_to_subscribed_fulltext |
| dc.identifier.citation | Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2012, v. 7287 LNCS, p. 385-399 [How to Cite?] DOI: http://dx.doi.org/10.1007/978-3-642-29952-0_38 |
| dc.identifier.doi | http://dx.doi.org/10.1007/978-3-642-29952-0_38 |
| dc.identifier.epage | 399 |
| dc.identifier.issn | 0302-9743 2011 SCImago Journal Rankings: 0.034 |
| dc.identifier.scopus | eid_2-s2.0-84861013577 |
| dc.identifier.spage | 385 |
| dc.identifier.uri | http://hdl.handle.net/10722/152043 |
| dc.identifier.volume | 7287 LNCS |
| dc.language | eng |
| dc.publisher | Springer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/ |
| dc.publisher.place | Germany |
| dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| dc.relation.references | References in Scopus |
| dc.subject | Data Aggregation |
| dc.subject | Physical Carrier Sensing |
| dc.subject | Sinr Interference Model |
| dc.title | Deterministic distributed data aggregation under the SINR model |
| dc.type | Conference_Paper |
Author Affiliations
- The University of Hong Kong
- Tsinghua University

