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Two-phase PT-Top


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Abstract

Uncertain data has become ubiquitous due to the development of Internet of Things (IOT) for collecting data in an imprecise way, such as in the dam safety monitoring applications. Efficient Top-k processing of uncertain data is an important requirement in the field of dam safety monitoring. In order to reduce energy consumption and query response time in the applications of IOTs, an uncertain data PT-Topk query processing scheme was studied in a hierarchical structural sensor network. Based on the x-tuple Rule of uncertain data, adopting intra-cluster and inter-cluster two phases query processing, a distributed Two-Phase PT-Topk Query Processing approximation algorithm (TPQP) was proposed. In the intra-cluster phase and inter-cluster phase, the local and global pruning upper bounds can be computed respectively. The data ranked lower than the two bounds cannot be forwarded to the sink node. Therefore, the proposed TPQP algorithm can reduce the transmission cost and shorten the query response time. The extensive experiment results demonstrate that TPQP can significantly reduce the transmission cost against the centralized algorithm by 87.51%, and shorten the query response time by 6%-31% and 35%-54% compared to BB and SSB, respectively. Meanwhile, TPQP can obtain the error rate below 5.5% in the different probability p and ranking number k.


Keywords


Pages

Total Pages: 8
Pages: 581-588

DOI
10.1080/10798587.2017.1316070


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Published

Volume: 23
Issue: 4
Year: 2017

Cite this document


References

Aggarwal, C.C., and P.S. Yu. "A Survey of Uncertain Data Algorithms and Applications." IEEE Transactions on Knowledge and Data Engineering 21.5 (2009): 609-623. Crossref. Web. https://doi.org/10.1109/TKDE.2008.190

Mohamed A.S. ACM Transactions on Database Systems

Mao Ye et al. "Distributed Processing of Probabilistic Top-k Queries in Wireless Sensor Networks." IEEE Transactions on Knowledge and Data Engineering 25.1 (2013): 76-91. Crossref. Web. https://doi.org/10.1109/TKDE.2011.145

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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