• Journal of KIISE:Databases
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• v.33 no.6
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• pp.631-643
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• 2006

Moving objects in a mobile environment to change their position based on the change of time require a query with their position as a basis. Efficient Regional Decision for Continuous Skyline Queries requires objectively pre-calculating the OSR(Optimal Skyline Region) regardless of the speed and direction of the moving objects. It proposes techniques to reduce the frequency of continuous queries by choosing a VCircle(Validity Circle) as safe location which has radius of the distance to the closest region with position on the moving object at center. But, a VCircle's area varies based on the Moving object's position from first marked time of continuous query. Therefore, the frequency of its continuous query is variable and also when the object moves inside of OSR, query can re-occur frequently In this paper, we suggest a technique of selecting an IVCircle(Interior Validity Circle) in a Skyline Region as the static Safe Region using the characteristics of the OSR. An Interior IVCircle can be calculated in advance when the OSR is decided. Our experiment shows that the frequency of using IVcircle as safe region reduced than that of using VCircle as safe region by 52.55%.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.344-347
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• 2008

본 논문에서 무선 방송 환경에서 효율적으로 스카이라인 질의를 처리하는 기법을 제안한다. 무선 방송 환경의 순차적 데이터 접근 특성 때문에 기존의 기법을 적용할 경우 접근시간 및 튜닝시간에 큰 제약이 있다. 이를 해결하고 모바일 사용자가 에너지 효율적으로 스카이라인 질의를 처리하기 위하여 DSI(Distributed Spatial Index) 구조에 기반한 SOA(Skyline On Air) 알고리즘을 제안하였다. 제안된 기법은 접근시간이 한 주기의 방송 프로그램 길이를 넘지 않도록 한다. 또한 성능 평가를 통하여 제안 된 기법이 접근시간 및 튜닝시간 측면에서 효율적임을 확인하였다.

• The Journal of Korean Association of Computer Education
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• v.18 no.5
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• pp.63-70
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• 2015

In the environment that the complex conditions need to be satisfied, skyline query have been applied to various field. To processing a skyline query in centralized scheme, several techniques have been suggested and recently map/reduce platform based approaches has been proposed which divides data space into multiple partitions for the vast volume of multidimensional data. However, the performances of these approaches are fluctuated due to the uneven data loading between servers and redundant tasks. Motivated by these issues, this paper suggests a novel technique called MR-DEAP which solves the uneven data loading using the random sampling. The experimental result gains the proposed MR-DEAP outperforms MR-Angular and MR-BNL scheme.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.12-21
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• 2010

Recently, "Service of information perspective" that is an important issue is that a company searches customers that interested in certain information and the company offers information to the customers. This service can gain high effects by low cost because of supporting selective information. In most recently, Reverse Skyline using Skyline Approximation(RSSA) is proposed to process services of information provider's perspective. RSSA has problem to defects about waste of processing time and memory. In this paper, Efficient Reverse Skyline(ERSL) Algorithm is proposed for Efficient processing the Skyline. ERSL is new Algorithm using Branch and Bound Skyline(BBS) reduces the waste of processing time and memory. When we execute the variety experimentation to valuation ERSL algorithm's capacity. It is proved the best efficient algorithm among the others because ERSL is flexibly kept the established capacity.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.741-744
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• 2015

최근 소셜 미디어를 이용한 대량의 데이터로부터 사용자의 의사결정을 지원하기위한 맞춤형 데이터 추천 서비스가 관심을 받고 있으며 사용자의 선호도에 근접한 데이터 추천기법으로 스카이라인 질의가 연구되어왔다. 그러나 기존의 스카이라인 질의는 데이터의 정적속성(위도, 경도, 가격 등)만을 기준으로 모든 사용자에게 동일한 데이터를 반환하기 때문에 맞춤형 데이터를 추천하기 어렵다. 본 논문에서는 사용자의 기호에 대한 정밀도를 높이기 위해 정적속성에서 동적속성(계산속성)을 유도하는 분기한정 동적 스카이라인 질의 기법(Branch and Bound Dynamic Skyline, BBDS)을 구현하였다. 시뮬레이션에서는 대규모 데이터 및 다양한 분포에 따른 실험을 수행한 결과 BBDS가 기존 기법에 비해 데이터 탐색과 추천에 있어서 향상된 성능을 나타내는 것으로 평가되었다.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.70-83
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• 2007

Most of works for skyline queries have focused on static data objects. With the advance in mobile applications, however, the need of continuous skyline queries for moving objects has been increasing. To process continuous skyline queries, the 4-phased decision method of skyline regions has been proposed recently. However, it is not feasible for a large number of data because of the high cost of computing skyline regions. To solve this problem, this paper first provides a theoretical analysis of the 4-phased decision method. Then we propose a progressive decision method of skyline regions for the 4-phased decision method, which consists of a distance-based pruning and an extent shrinking of region decision lines. The proposed method can efficiently reduce the cost of the decision of skyline region in the 4-phased decision method. This paper also presents the experimental results to show the effectiveness of the proposed method.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.17-24
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• 2020

The traveling salesman problem is an algorithmic problem tasked with finding the shortest route that a salesman visits, visiting each city and returning to the started city. Due to the exponential time complexity of TSP, it's hard to implement on cases like amusement park or delivery. Also, TSP is hard to meet user's demand that is associated with multi-dimensional attributes like travel time, interests, waiting time because it uses only one attribute - distance between nodes. This paper proposed Top-n Skyline-Multi Dimension TSP to resolve formerly adverted problems. The proposed algorithm finds the shortest route faster than the existing method by decreasing the number of operations, selecting multi-dimensional nodes according to the dominance of skyline. In the simulation, we compared computation time of dynamic programming algorithm to the proposed a TS-MDT algorithm, and it showed that TS-MDT was faster than dynamic programming algorithm.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.280-291
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• 2009

Skyline Query processing is important to wireless sensor applications in order to process multi-dimensional data efficiently. Most skyline researches about sensor network focus on minimizing the energy consumption due to the battery powered constraints. In order to reduce energy consumption, Filtering Method is proposed. Most existing researches have assumed a snapshot skyline query processing and do not consider continuous queries and use data generated in ancestor node. In this paper, we propose an energy efficient method called Bottom up filtering tuple selection for continuous skyline query processing. Past skyline data generated in child nodes are stored in each sensor node and is used when choosing filtering tuple. We also extend the algorithms, called Support filtering tuple(SFT) that is used when we choose the additional filtering tuple. There is a temporal correlation between previous sensing data and recent sensing data. Thus, Based on past data, we estimate current data. By considering this point, we reduce the unnecessary communication cost. The experimental results show that our method outperforms the existing methods in terms of both data reduction rate(DRR) and total communication cost.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.938-942
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• 2009

In this paper, we propose a novel filtering method for processing continuous skyline queries on wireless sensor network environments. The existing filtering methods use the filter based on router paths. However, because these filters are applied not to a whole area but to a partial area, these methods send almost data of sensor nodes to transmit to the base station and have no sufficient effect in terms of energy efficiency. Therefore, we propose an efficient method to dramatically reduce the transmission data of sensors through applying a low-cost and effective filter to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.