Abstract
Data and storage management is turning to distributed due to the huge increase in data volumes. To satisfy users’ requirements and preferences, advanced query operators, such as skyline, have been introduced and implemented. Skyline offers users with interesting objects, which has been explored in centralized, distributed and peer-to-peer (P2P) systems. However, keyword-matched skyline has not been considered in distributed and P2P systems. This paper introduces keyword-matched data skyline algorithms in P2P systems. Differing from other operators, skyline algorithms are devised to exploit its properties to reduce traversed peers for a query. By partitioning data space and using distributed hash tables (DHTs) and Bloom filters, we design new algorithms, Nk-sky and Ck-sky, to reduce the required traversed peers to answer keyword-matched data skyline queries. We apply the algorithms on Chord as an example of DHT overlay P2P systems. Experimental results show a significant reduction of traversed peers with the Cover-set tuples algorithm Ck-sky.
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Banafaa, K.M., Li, R., Wen, K., Gu, X., Li, Y. (2013). Keyword-Matched Data Skyline in Peer-to-Peer Systems. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds) Database Systems for Advanced Applications. DASFAA 2013. Lecture Notes in Computer Science, vol 7825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37487-6_8
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