Query Processing Methods for Connectivity Search in Visual Databases Using R+-tree

The data stream is a series of data generated at sequential time from different sources. Processing such data is very important in many contemporary applications such as sensor networks, RFID technology, mobile computing and many more. The huge amount data generated and frequent changes in a short time makes the conventional processing methods insufficient. The Sliding Window Model (SWM) was introduced by Datar et. al to handle this problem. Avoiding multiple scans of the whole data sets, optimizing memory usage, and processing only the most recent tuple are the main challenges. The number of possible world instances grows exponentially in uncertain data and it is highly difficult to comprehend what it takes to meet Top-k query processing in the shortest amount of time. Following the generation of rules and the probability theory of this model, a framework was anticipated to sustain top-k processing algorithm over the SWM approach until the candidates expired. Based on the literature review study, none of the existing work have been made to tackle the issue arises from the top-k query processing of the possible world instance of the uncertain data streams within the SWM. The major issue resulted from these scenarios need to be addressed especially in the computation redundancy area that contributed to the increases of computational cost within the SWM. Therefore, the main objective of this research work is to propose the top-k query processing methods over uncertain data streams in SWM utilizing the score and the Possible World (PW) setting. In this study, a novel expiration and object indexing method is introduced to address the computational redundancy issues. We believed the proposed method can reduce computational costs and by managing insertion and exit policy on the right tuple candidates within a specified window frame. This research work will contribute to the area of computational query processing.

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Query Processing of Geosocial Data in Location-Based Social Networks

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi11010019 ◽

2021 ◽

Vol 11 (1) ◽

pp. 19

Author(s):

Arianna D’Ulizia ◽

Patrizia Grifoni ◽

Fernando Ferri

Keyword(s):

Query Processing ◽

Future Perspectives ◽

Access Method ◽

Processing Methods ◽

Data Representations ◽

The Common ◽

Use Of Social Media ◽

Location Based Social Networks ◽

Evaluation Approaches ◽

Near Future

The increasing use of social media and the recent advances in geo-positioning technologies have produced a great amount of geosocial data, consisting of spatial, textual, and social information, to be managed and queried. In this paper, we focus on the issue of query processing by providing a systematic literature review of geosocial data representations, query processing methods, and evaluation approaches published over the last two decades (2000–2020). The result of our analysis shows the categories of geosocial queries proposed by the surveyed studies, the query primitives and the kind of access method used to retrieve the result of the queries, the common evaluation metrics and datasets used to evaluate the performance of the query processing methods, and the main open challenges that should be faced in the near future. Due to the ongoing interest in this research topic, the results of this survey are valuable to many researchers and practitioners by gaining an in-depth understanding of the geosocial querying process and its applications and possible future perspectives.

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K-Nearest Neighbor query processing methods in road network space: Performance evaluation

2009 IEEE International Conference on Network Infrastructure and Digital Content ◽

10.1109/icnidc.2009.5360949 ◽

2009 ◽

Cited By ~ 1

Author(s):

Sung-Hyun Shin ◽

Sang-Chul Lee ◽

Sang-Wook Kim ◽

Junghoon Lee ◽

Eul Gyu Lim

Keyword(s):

Performance Evaluation ◽

Query Processing ◽

Road Network ◽

Nearest Neighbor ◽

K Nearest Neighbor ◽

Processing Methods ◽

Nearest Neighbor Query ◽

Network Space

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Performance and scalability of indexed subgraph query processing methods

Proceedings of the VLDB Endowment ◽

10.14778/2824032.2824054 ◽

2015 ◽

Vol 8 (12) ◽

pp. 1566-1577 ◽

Cited By ~ 15

Author(s):

Foteini Katsarou ◽

Nikos Ntarmos ◽

Peter Triantafillou

Keyword(s):

Query Processing ◽

Processing Methods ◽

Subgraph Query

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Verification of Super-Peer Model for Query Processing in Peer-to-Peer Networks

Innovative Research and Applications in Next-Generation High Performance Computing - Advances in Systems Analysis, Software Engineering, and High Performance Computing ◽

10.4018/978-1-5225-0287-6.ch012 ◽

2016 ◽

pp. 306-332

Author(s):

J. Pourqasem ◽

S.A. Edalatpanah

Keyword(s):

Distributed Systems ◽

Query Processing ◽

Large Scale ◽

Peer To Peer ◽

P2p Networks ◽

Processing Methods ◽

Super Node ◽

And Performance ◽

Processing Techniques ◽

Super Peer

Equal peers in peer-to-peer (P2P) networks are the drawbacks of system in term of bandwidth, scalability and efficiency. The super-peer model is based on heterogeneity and different characteristics of peers in P2P networks. The P2P networks and large- scale distributed systems based on P2P networks use the super-peer model to design the query processing mechanism. This chapter first reviews the query processing methods in P2P networks, in which the authors classify theses query processing approaches in Unstructured and Structured mechanisms. Furthermore, the query processing techniques in distributed systems based on P2P networks are discussed. Afterward, authors concentrate on super-peer model to process the query of peers in P2P networks. Authors present the query processing methods in P2P-based distributed systems using the super node. Finally, the chapter provides some examples of each of the presented query processing techniques, and then illustrates the properties of each of them in terms of scalability and performance issues.

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