• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.7-18
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• 2012

It has been studied to support data having multiple properties, called Skyline Query. The skyline query is not exploring data having all properties but only meaningful data, when we retrieve informations in large data base. The skyline query can be used to provide some information about various environments and situations in sensor network. However, the legacy skyline query has a problem that increases the number of comparisons as the number of sensors are increasing in multi-dimensional data. Also important values are often omitted. Therefore, we propose a new method to reduce the complexity of comparison where the large number of sensors are placed. To reduce the complexity, we transfer a CMF(Category Based Member Function) which can identify preference of specific data when interest query from sync-node is transferred to sub-node. To show the validity of our method, we analyzed the performance by simulations. As a result, it showed that the time complexity was reduced when we retrieved information in multiple sensing data and omitted values are detected by great dominance Skyline.

• 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%.

• The KIPS Transactions:PartD
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• v.17D no.4
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• pp.245-252
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• 2010

In this paper, we propose an effective filtering method for skyline queries in mobile ad hoc networks (MANETs). Most existing researches assume that data is uniformly distributed. Under these assumptions, the previous works focus on optimizing the energy consumption due to the limited battery power. However, in practice, data distribution is skewed in a specific region. In order to reduce the energy consumption, we propose a new filtering method considering the data distribution. We verify the performance of the proposed method through a comparative experiment with an existing method. The results of the experiment confirm that the proposed method reduces the communication overhead and execution time compared to an existing method.

• 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.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.35-36
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• 2015

본 논문에서는 모바일 P2P 네트워크에서 스카이라인 질의 처리를 위한 새로운 필터링 기법을 제안한다. 제안하는 기법에서는 질의처리 이전에 스카이라인 처리를 통해 필터링 객체 셋을 생성하기 위해 피어 간 데이터 배포를 수행한다. 생성된 필터링 객체를 활용하여 질의에 참여하는 객체 중 불필요한 객체를 필터링한다. 사전 스카이라인 처리를 통해 효율적인 질의처리를 수행할 수 있다.

• Journal of KIISE:Databases
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• v.37 no.4
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• pp.185-196
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• 2010

Existing methods to compute reverse skyline queries are not correct to process the queries in dataset with region objects which have conditions like a price is 5~7 dollars and a distance to beach is 1km~2km, since they consider datasets with only point objects. To solve the problem, we propose a novel method to process reverse skyline queries for region objects in this paper. It has advantages. First, it is expected to get a good performance, because it is extended from efficient reverse skyline (ERSL) algorithm which is a best algorithm to computing reverse skyline queries in datasets with point objects. Second, it can give a right of choice unlike the others to a person requesting the query. That is because results of reverse skyline have a difference preference according to proposed pruning methods and overlap relations. This algorithm is a first for supporting region objects. Therefore there are not any other algorithms to compare their performance. For that reason, our experiment to prove the efficiency of proposed algorithm is focused what conditions give an effect to its performance and result and how much time it needs to process the query.

• 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.

• 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.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.476-485
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• 2009

In sensor networks, many methods have been proposed to process in-network aggregation effectively. Unlike general aggregation queries, skyline query processing compares multi-dimensional data for the result. Therefore, it is very difficult to process the skyline queries in sensor networks. It is important to filter unnecessary data for energy-efficient skyline query processing. Existing approach like MFTAC restricts unnecessary data transitions by deploying filters to whole sensors. However, network lifetime is reduced by energy consumption for many false positive data and filters transmission. In this paper, we propose a bottom up filtering-based skyline query processing algorithm of in-network for reducing energy consumption by filters transmission and a PBFiltering technique for improving performance of filtering. The proposed algorithm creates the skyline filter table (SFT) in the data gathering process which sends from sensor nodes to the base station and filters out unnecessary transmissions using it. The experimental results show that our algorithm reduces false positives and improves the network lifetime over the existing method.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.829-830
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• 2017

스카이라인 질의는 '지배(dominate)'관계를 적용한 선호도 질의(preference query)의 한 종류로, 복수의 기준을 이용한 의사 결정 시 사용된다. 스카이라인 질의 결과는 다수의 선택지 중에서 사용자가 다른 객체에 비해 뒤처지지 않는 선택지를 제시함으로써 사용자가 검토해야하는 선택지의 수를 대폭 감소시키기 때문에 대용량 데이터 분석 시 매우 유용하게 활용될 수 있다. 본 논문에서는 기존에 제시된 BBS(Branch and Bound Skyline Computation)에서 사용되고 있는 평가함수를 설명하고, 스카이라인 계산을 위해 사용할 수 있는 대안 평가함수의 속성을 제시한다. 또한 다양한 대안 평가함수를 사용한 실험을 통해 성능을 분석했으며, 이를 통해 기존 기법의 성능보다 좋은 평가함수가 존재함을 보였다.