Energy-Efficient β-Approximate Skylines Processing in Wireless Sensor Networks. (25th February 2015)
- Record Type:
- Journal Article
- Title:
- Energy-Efficient β-Approximate Skylines Processing in Wireless Sensor Networks. (25th February 2015)
- Main Title:
- Energy-Efficient β-Approximate Skylines Processing in Wireless Sensor Networks
- Authors:
- Xin, Junchang
Wang, Zhiqiong
Bai, Mei
Ding, Linlin
Wang, Guoren - Other Names:
- Turetsky Vladimir Academic Editor.
- Abstract:
- Abstract : As the first priority of query processing in wireless sensor networks is to save the limited energy of sensor nodes and in many sensing applications a part of skyline result is enough for the user's requirement, calculating the exact skyline is not energy-efficient relatively. Therefore, a new approximate skyline query, β -approximate skyline query which is limited by a guaranteed error bound, is proposed in this paper. With an objective to reduce the communication cost in evaluating β -approximate skyline queries, we also propose an energy-efficient processing algorithm using mapping and filtering strategies, named Actual Approximate Skyline (AAS). And more than that, an extended algorithm named Hypothetical Approximate Skyline (HAS) which replaces the real tuples with the hypothetical ones is proposed to further reduce the communication cost. Extensive experiments on synthetic data have demonstrated the efficiency and effectiveness of our proposed approaches with various experimental settings.
- Is Part Of:
- Mathematical problems in engineering. Volume 2015(2015)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2015(2015)
- Issue Display:
- Volume 2015, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 2015
- Issue:
- 2015
- Issue Sort Value:
- 2015-2015-2015-0000
- Page Start:
- Page End:
- Publication Date:
- 2015-02-25
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2015/149513 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10331.xml