Processing relaxed skylines in PDMS using distributed data summaries

Abstract

Peer Data Management Systems (PDMS) are a natural extension of heterogeneous database systems. One of the main tasks in such systems is efficient query processing. Insisting on complete answers, however, leads to asking almost every peer in the network. Relaxing these completeness requirements by applying approximate query answering techniques can significantly reduce costs. Since most users are not interested in the exact answers to their queries, rank-aware query operators like top-k or skyline play an important role in query processing. In this paper, we present the novel concept of relaxed skylines that combines the advantages of both rank-aware query operators and approximate query processing techniques. Furthermore, we propose a strategy for processing relaxed skylines in distributed environments that allows for giving guarantees for the completeness of the result using distributed data summaries as routing indexes.

Efficient execution plans for distributed skyline query processing

“…Skyline computation [4] has recently attracted considerable attention and has been studied in a variety of distributed systems, including web information systems [3], parallel systems [17], peer-to-peer systems [5,10,13,18,19,[21][22][23], mobile ad-hoc networks [14,20], as well as more generic distributed systems [7,16,24]. In the following, we provide an overview of existing approaches for distributed skyline computation.…”

“…Hose et al [13] use distributed data summaries for efficient processing of approximate skyline queries and provide guarantees for the completeness of the result. Skyline computation over a superpeer architecture has been studied in [18,19].…”

“…The houses in the skyline set are those that are not worse than (not dominated by) any other house in both price and distance. Skyline queries have been studied both in centralized and distributed environments [3][4][5]7,10,13,14,16,18,[20][21][22][23][24]. However, planning the execution of skyline queries on different (potentially overlapping) data fractions, in order to obtain the skyline set of the entire dataset efficiently, has not received adequate attention in the related work.…”

Angle-based space partitioning for efficient parallel skyline computation

“…There has been a growing interest in distributed [1,7,12,18,19] and parallel [5,6,21] skyline computation lately. In [1,12], skyline processing is studied over distributed web sources.…”

“…Parallel query processing attempts to alleviate some of the deficiencies of such problematic situations and has been explored by the database research community for other operators such as joins, nearest neighbor queries, etc. Although the skyline operator has been thoroughly investigated in centralized settings [2,4,10,14,17], only recently parallel [5,6,21] and distributed [1,7,18,19] skyline query processing has attracted attention.…”