• Title/Summary/Keyword: Location-based Query Processing

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Reverse k-Nearest Neighbor Query Processing Method for Continuous Query Processing in Bigdata Environments (빅데이터 환경에서 연속 질의 처리를 위한 리버스 k-최근접 질의 처리 기법)

  • Lim, Jongtae;Park, Sunyong;Seo, Kiwon;Lee, Minho;Bok, Kyoungsoo;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.14 no.10
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    • pp.454-462
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    • 2014
  • With the development of location aware technologies and mobile devices, location-based services have been studied. To provide location-based services, many researchers proposed methods for processing various query types with Mapreduce(MR). One of the proposed methods, is a Reverse k-nearest neighbor(RkNN) query processing method with MR. However, the existing methods spend too much cost to process the continuous RkNN query. In this paper, we propose an efficient continuous RkNN query processing method with MR to resolve the problems of the existing methods. The proposed method uses the 60-degree-pruning method. The proposed method does not need to reprocess the query for continuous query processing because the proposed method draws and monitors the monitoring area including the candidate objects of a RkNN query. In order to show the superiority of the proposed method, we compare it with the query processing performance of the existing method.

A Nearest Neighbor Query Processing Algorithm Supporting K-anonymity Based on Weighted Adjacency Graph in LBS (위치 기반 서비스에서 K-anonymity를 보장하는 가중치 근접성 그래프 기반 최근접 질의처리 알고리즘)

  • Jang, Mi-Young;Chang, Jae-Woo
    • Spatial Information Research
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    • v.20 no.4
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    • pp.83-92
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    • 2012
  • Location-based services (LBS) are increasingly popular due to the improvement of geo-positioning capabilities and wireless communication technology. However, in order to enjoy LBS services, a user requesting a query must send his/her exact location to the LBS provider. Therefore, it is a key challenge to preserve user's privacy while providing LBS. To solve this problem, the existing method employs a 2PASS cloaking framework that not only hides the actual user location but also reduces bandwidth consumption. However, 2PASS does not fully guarantee the actual user privacy because it does not take the real user distribution into account. Hence, in this paper, we propose a nearest neighbor query processing algorithm that supports K-anonymity property based on the weighted adjacency graph(WAG). Our algorithm not only preserves the location of a user by guaranteeing k-anonymity in a query region, but also improves a bandwidth usage by reducing unnecessary search for a query result. We demonstrate from experimental results that our algorithm outperforms the existing one in terms of query processing time and bandwidth usage.

Efficient k-Nearest Neighbor Query Processing Method for a Large Location Data (대용량 위치 데이터에서 효율적인 k-최근접 질의 처리 기법)

  • Choi, Dojin;Lim, Jongtae;Yoo, Seunghun;Bok, Kyoungsoo;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.17 no.8
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    • pp.619-630
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    • 2017
  • With the growing popularity of smart devices, various location based services have been providing to users. Recently, some location based social applications that combine social services and location based services have been emerged. The demands of a k-nearest neighbors(k-NN) query which finds k closest locations from a user location are increased in the location based social network services. In this paper, we propose an approximate k-NN query processing method for fast response time in a large number of users environments. The proposed method performs efficient stream processing using big data distributed processing technologies. In this paper, we also propose a modified grid index method for indexing a large amount of location data. The proposed query processing method first retrieves the related cells by considering a user movement. By doing so, it can make an approximate k results set. In order to show the superiority of the proposed method, we conduct various performance evaluations with the existing method.

An Efficient Continuous Reverse Skyline Query Processing Method in Metric Spaces for Location-based Services (위치기반 서비스를 위한 거리공간에서의 효율적인 연속 리버스 스카이라인 질의 처리 기법)

  • Lim, Jong-Tae;Park, Yong-Hun;Seo, Dong-Min;Yoo, Jae-Soo
    • Journal of KIISE:Databases
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    • v.37 no.5
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    • pp.250-257
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    • 2010
  • As the variant of skyline query processing, reverse skyline Queries have been studied. However, the existing methods for processing reverse skyline Queries have the limitation of service domains and spend high costs to provide various location-based services. In this paper, we propose a new reverse skyline Query processing method that efficiently processes a query with the objects in metric spaces. In addition, the proposed method also processes continuous reverse skyline queries efficiently. In order to show the superiority of the proposed scheme, we compare it with the previous reverse skyline 벼ery processing scheme in various environments. As a result, the proposed method achieves better performance than the existing method.

Closest Pairs and e-distance Join Query Processing Algorithms using a POI-based Materialization Technique in Spatial Network Databases (공간 네트워크 데이터베이스에서 POI 기반 실체화 기법을 이용한 Closest Pairs 및 e-distance 조인 질의처리 알고리즘)

  • Kim, Yong-Ki;Chang, Jae-Woo
    • Journal of Korea Spatial Information System Society
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    • v.9 no.3
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    • pp.67-80
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    • 2007
  • Recently, many studies on query processing algorithms has been done for spatial networks, such as roads and railways, instead of Euclidean spaces, in order to efficiently support LBS(location-based service) and Telematics applications. However, both a closest pairs query and an e-distance join query require a very high cost in query processing because they can be answered by processing a set of POIs, instead of a single POI. Nevertheless, the query processing cost for closest pairs and e-distance join queries is rapidly increased as the number of k (or the length of radius) is increased. Therefore, we propose both a closest pairs query processing algorithm and an e-distance join query processing algorithm using a POI-based materialization technique so that we can process closest pairs and e-distance join queries in an efficient way. In addition, we show the retrieval efficiency of the proposed algorithms by making a performance comparison of the conventional algorithms.

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Range Query Processing of Distributed Moving Object Databases using Scheduling Technique (스케쥴링 기법을 이용한 분산 이동 객체 데이타베이스의 범위 질의 처리)

  • Jeon, Se-Gil;Hwang, Jae-Il;Nah, Youn-Mook
    • Journal of Korea Spatial Information System Society
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    • v.6 no.2 s.12
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    • pp.51-62
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    • 2004
  • Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries. To improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structures of GALIS architecture,which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

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An Efficient Range Query Processing of Distributed Moving Object (분산 이동 객체 데이터베이스의 효율적인 범위 질의 처리)

  • Jeon, Se-Gil;Woo, Chan-Il
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.42 no.1
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    • pp.35-40
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    • 2005
  • Recently, the location based service for moving customers is becoming one of the most important service in mobile communication area and for moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries and to improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structure, which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

In-Route Nearest Neighbor Query Processing Algorithm with Time Constraint in Spatial Network Databases (공간 네트워크 데이터베이스에서 시간제약을 고려한 경로 내 최근접 질의처리 알고리즘)

  • Kim, Yong-Ki;Kim, Sang-Mi;Chang, Jae-Woo
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.2
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    • pp.196-200
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    • 2008
  • Recently, the query processing algorithm in spatial network database (SNDB) has attracted many interests. However, there is little research on route-based query processing algorithm in SNDB. Since the moving objects moves only in spatial networks, the route-based algorithm is very useful for LBS and Telematics applications. In this paper, we analyze In-Route Nearest Neighbor (IRNN) query, which is an typical one of route-based queries, and propose a new IRNN query processing algorithm with time constraint. In addition, we show from our performance analysis that our IRNN query processing algorithm with time constraint is better on retrieval performance than the existing IRNN query processing one.

Range and k-Nearest Neighbor Query Processing Algorithms using Materialization Techniques in Spatial Network Databases (공간 네트워크 데이터베이스에서 실체화 기법을 이용한 범위 및 k-최근접 질의처리 알고리즘)

  • Kim, Yong-Ki;Chowdhury, Nihad Karim;Lee, Hyun-Jo;Chang, Jae-Woo
    • Journal of Korea Spatial Information System Society
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    • v.9 no.2
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    • pp.67-79
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    • 2007
  • Recently, to support LBS(location-based services) and telematics applications efficiently, there have been many researches which consider the spatial network instead of Euclidean space. However, existing range query and k-nearest neighbor query algorithms show a linear decrease in performance as the value of radius and k is increased. In this paper, to increase the performance of query processing algorithm, we propose materialization-based range and k-nearest neighbor algorithms. In addition, we make the performance comparison to show the proposed algorithm achieves better retrieval performance than the existing algorithm.

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Hilbert-curve based Multi-dimensional Indexing Key Generation Scheme and Query Processing Algorithm for Encrypted Databases (암호화 데이터를 위한 힐버트 커브 기반 다차원 색인 키 생성 및 질의처리 알고리즘)

  • Kim, Taehoon;Jang, Miyoung;Chang, Jae-Woo
    • Journal of Korea Multimedia Society
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    • v.17 no.10
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    • pp.1182-1188
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    • 2014
  • Recently, the research on database outsourcing has been actively done with the popularity of cloud computing. However, because users' data may contain sensitive personal information, such as health, financial and location information, the data encryption methods have attracted much interest. Existing data encryption schemes process a query without decrypting the encrypted databases in order to support user privacy protection. On the other hand, to efficiently handle the large amount of data in cloud computing, it is necessary to study the distributed index structure. However, existing index structure and query processing algorithms have a limitation that they only consider single-column query processing. In this paper, we propose a grid-based multi column indexing scheme and an encrypted query processing algorithm. In order to support multi-column query processing, the multi-dimensional index keys are generated by using a space decomposition method, i.e. grid index. To support encrypted query processing over encrypted data, we adopt the Hilbert curve when generating a index key. Finally, we prove that the proposed scheme is more efficient than existing scheme for processing the exact and range query.