Grid‐PPPS: A Skyline Method for Efficiently Handling Top‐k Queries in Internet of Things

Sun-Young Ihm, Aziz Nasridinov and Young-Ho Park

Journal of Applied Mathematics, 2014, vol. 2014, issue 1

Abstract: A rapid development in wireless communication and radio frequency technology has enabled the Internet of Things (IoT) to enter every aspect of our life. However, as more and more sensors get connected to the Internet, they generate huge amounts of data. Thus, widespread deployment of IoT requires development of solutions for analyzing the potentially huge amounts of data they generate. A top‐k query processing can be applied to facilitate this task. The top‐k queries retrieve k tuples with the lowest or the highest scores among all of the tuples in the database. There are many methods to answer top‐k queries, where skyline methods are efficient when considering all attribute values of tuples. The representative skyline methods are soft‐filter‐skyline (SFS) algorithm, angle‐based space partitioning (ABSP), and plane‐project‐parallel‐skyline (PPPS). Among them, PPPS improves ABSP by partitioning data space into a number of spaces using hyperplane projection. However, PPPS has a high index building time in high‐dimensional databases. In this paper, we propose a new skyline method (called Grid‐PPPS) for efficiently handling top‐k queries in IoT applications. The proposed method first performs grid‐based partitioning on data space and then partitions it once again using hyperplane projection. Experimental results show that our method improves the index building time compared to the existing state‐of‐the‐art methods.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1155/2014/401618

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2014:y:2014:i:1:n:401618

Access Statistics for this article

More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().