TY - GEN
T1 - Progressive skyline query processing in wireless sensor networks
AU - Chen, Baichen
AU - Liang, Weifa
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2009
Y1 - 2009
N2 - With the further development of sensor techniques in wireless sensor networks (WSNs), it is becoming urgent that they should be able to support complicated queries like skyline query for multi-preference and decision making. In this paper, we consider skyline query evaluation in WSNs by devising evaluation algorithms for finding skyline points on a dataset progressively. The core techniques adopted are to partition the dataset into several disjoint subsets and output the skyline points by examining each subsequent subset progressively, using some of the skyline points obtained so far to filter out those unlikely skyline points in the current processing subset from transmission. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms on synthetic and real datasets. The experimental results show that the proposed algorithms outperform existing algorithms significantly in network lifetime prolongation. © 2009 IEEE.
AB - With the further development of sensor techniques in wireless sensor networks (WSNs), it is becoming urgent that they should be able to support complicated queries like skyline query for multi-preference and decision making. In this paper, we consider skyline query evaluation in WSNs by devising evaluation algorithms for finding skyline points on a dataset progressively. The core techniques adopted are to partition the dataset into several disjoint subsets and output the skyline points by examining each subsequent subset progressively, using some of the skyline points obtained so far to filter out those unlikely skyline points in the current processing subset from transmission. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms on synthetic and real datasets. The experimental results show that the proposed algorithms outperform existing algorithms significantly in network lifetime prolongation. © 2009 IEEE.
KW - Energy conservation
KW - Progressive algorithms
KW - Query optimization
KW - Skyline query
KW - Wireless sensor network
UR - https://www.scopus.com/pages/publications/77949929464
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-77949929464&origin=recordpage
U2 - 10.1109/MSN.2009.43
DO - 10.1109/MSN.2009.43
M3 - RGC 32 - Refereed conference paper (with host publication)
T3 - MSN 2009 - 5th International Conference on Mobile Ad-hoc and Sensor Networks
SP - 17
EP - 24
BT - MSN 2009 - 5th International Conference on Mobile Ad-hoc and Sensor Networks
T2 - 5th International Conference on Mobile Ad-hoc and Sensor Networks, MSN 2009
Y2 - 14 December 2009 through 16 December 2009
ER -