A Model for Skyline Query Processing in a Partially Complete Database

Gulzar, Yonis; Alwan, Ali A.; Salleh, Norsaremah; Alyaseen, Imad Fakhri Taha

doi:10.1166/asl.2018.10745

Cited by 10 publications

(5 citation statements)

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“…Eventually, the dominance test process ends up with a result that depicts b1 dominates b2, b2 dominates b3, and b3 dominates b1 and retrieves an empty set of skylines. Most importantly, we also observed that most of the previous works assumed that the contents of the database are static and update operations such as insert are very infrequent [24], [26], [27], [29], [30], [32]- [35]. However, the update operation is among the indispensable operations in database systems.…”

Section: Introductionmentioning

confidence: 78%

IDSA: An Efficient Algorithm for Skyline Queries Computation on Dynamic and Incomplete Data With Changing States

et al. 2021

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Skyline queries have been widely used as an effective query tool in many contemporary database applications. The main concept of skyline queries relies on retrieving the non-dominated tuples in the database which are known skylines. In most database applications, the contents of the databases are dynamic due to the continuous changes made towards the database. Typically, the changes in the contents of the database occur through data manipulation operations (INSERT and/or UPDATE). Performing these operations on the database results in invalidating the most recent skylines before changes are made on the database. Furthermore, the presence of incomplete data in databases becomes frequent phenomena in recent database applications. Data incompleteness causes several challenges on skyline queries such as losing the transitivity property of the skyline technique and the test dominance process between tuples being cyclic. Reapplying skyline technique on the entire updated incomplete database to determine the new skylines is unwise due to the exhaustive pairwise comparisons. Thus, this paper proposes an approach, named Incomplete Dynamic Skyline Algorithm (IDSA) which attempts to determine the skylines on dynamic and incomplete databases. Two optimization techniques have been incorporated in IDSA, namely: pruning and selecting superior local skylines. The pruning process attempts to exploit the derived skylines before the INSERT/UPDATE operation made on the database to identify the new skylines. Moreover, selecting superior local skylines process assists in further eliminating the remaining non-skylines from further processing. These two optimization techniques lead to a large reduction in the number of domination tests due to avoiding recomputing of skylines over the entire updated database to derive the new skylines. Extensive experiments have been accomplished on both real and synthetic datasets, and the results demonstrate that IDSA outperforms the existing solutions in terms of the number of domination tests and the processing time of the skyline operation.INDEX TERMS Dynamic database, incomplete database, pairwise comparison, skyline queries.

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Section: Introductionmentioning

confidence: 78%

IDSA: An Efficient Algorithm for Skyline Queries Computation on Dynamic and Incomplete Data With Changing States

et al. 2021

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“…In the last part of the experiment set, the amount of data transferred from one data center to another is measured. It is proven from the literature that these parameters are the most crucial parameters that influence skyline query processing [1], [2], [4], [13], [23], [36], [44], [45].…”

Section: A Experimental Resultsmentioning

confidence: 99%

CIDS: An Efficient Algorithm for Processing Skyline Queries for Partially Complete Data in Cloud Environment

Gulzar

Alwan

2022

IEEE Access

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From a set of existing tuples, a skyline operator retrieves only a subset, superior tuples that are of a person's interest and are non-dominant. Processing of queries using the skyline operator is an expensive and exhaustive task. It gets more complicated when skyline queries are applied on partially complete data and databases are distributed over different data centers. Incompleteness in data raises many issues such as compromise on transitivity property and the threat of cyclic dominance to occur within database. To overcome such issues this paper proposes an efficient algorithm called Cloud-based Incomplete Data Skyline algorithm (CIDS) for processing skyline queries over partially complete databases in cloud environment. The algorithm retrieves superior tuples with the aim of reducing domination tests between the tuples, decreasing processing time and reducing the huge amount of data flow from one data center to another. Several experiments have been conducted over different types of datasets, and results have proven that the proposed algorithm outplays the existing algorithms in terms of processing time, domination tests as well as the amount of data flow.

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“…Several works on skyline computation have been inspired due to the benefits that can be achieved if applications for retrieving non-trivial information are developed [1], [2], [4], [5], [6], [7], [8], [9], [14], [15], [16], [19], [22], [25], [26], [27], [31], [36], [39], [44]. Recently, skyline queries have received considerable attention in databases [39], [41], [46].…”

Section: Related Workmentioning

confidence: 99%

“…Inspired by the work of [29], [26] proposed the SkyQU D framework, a non-index based skyline analysis on high-dimensional data with uncertain dimensions. This framework, efficiently process skyline queries by evaluating the skylines through three distinct methods that guarantee the probability of each object being in the final skyline results.…”

Section: Work On Skyline Query That Adopted the Non-index Based Approachmentioning

confidence: 99%

Computing Skylines Over Uncertain Data

Lawal

Ibrahim²,

Sani³

et al. 2022

SSRN Journal

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A Model for Skyline Query Processing in a Partially Complete Database

Cited by 10 publications

References 0 publications

IDSA: An Efficient Algorithm for Skyline Queries Computation on Dynamic and Incomplete Data With Changing States

IDSA: An Efficient Algorithm for Skyline Queries Computation on Dynamic and Incomplete Data With Changing States

CIDS: An Efficient Algorithm for Processing Skyline Queries for Partially Complete Data in Cloud Environment

Computing Skylines Over Uncertain Data

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