• Journal of Korea Spatial Information System Society
• /
• v.12 no.1
• /
• pp.18-27
• /
• 2010

In u-GIS environment, GeoSensor environment requires that dynamic data captured from various sensors and static information in terms of features in 2D or 3D are fused together. GeoSensors, the core of this environment, are distributed over a wide area sporadically, and are collected in any size constantly. As a result, storage space could be exceeded because of restricted memory in DSMS. To solve this kind of problems, a lot of related studies are being researched actively. There are typically 3 different methods - Random Load Shedding, Semantic Load Shedding, and Sampling. Random Load Shedding chooses and deletes data in random. Semantic Load Shedding prioritizes data, then deletes it first which has lower priority. Sampling uses statistical operation, computes sampling rate, and sheds load. However, they are not high accuracy because traditional ones do not consider spatial characteristics. In this paper 'Pre-Filtering based Post Load Shedding' are suggested to improve the accuracy of spatial query and to restrict load shedding in DSMS. This method, at first, limits unnecessarily increased loads in stream queue with 'Pre-Filtering'. And then, it processes 'Post-Load Shedding', considering data and spatial status to guarantee the accuracy of result. The suggested method effectively reduces the number of the performance of load shedding, and improves the accuracy of spatial query.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.12
• /
• pp.8370-8377
• /
• 2015

In spatial data stream management systems, it is needed appropriate load shedding algorithm because real-time input spatial data streams could exceed the limitation of main memory. However previous researches, lack regard for input ratio and spatial utilization rates of spatial data streams, or the characteristics of data source which generates data streams with spatial information efficiently, can lead to decrease the performance and accuracy of spatial data stream query. Therefore, multi-level load shedding scheme for spatial data stream management systems is proposed to increase the spatial query performance and accuracy. This proposed scheme limits overloads in relation to the input rate and the characteristics of data source first, and then, if needed, query data representing low query participation probability based on spatial utilizations are dropped relatively. Our experiments show that the proposed method could decrease load shedding frequency for previous researches by more than 11% despite query results accuracy and query performance are superior at 0.04% and 3%.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.89-98
• /
• 2009

As data stream is entered into system continuously and the memory space is limited, the data exceeding the memory size cannot be processed. In order to solve the problem, load shedding methods which drop a part of data to prevent exceeding the storage space have been researched. Generally, a traditional load shedding method uses random sampling with optimized rate according to data deviation. The method samples data not to distinguish those used in spatial query because the method uses only a random sampling with optimized rate according to data deviation. Therefore, the accuracy of query was reduced in u-GIS environment including spatial query. In this paper, we researched a new load shedding method improving accuracy of the query in u-GIS environment which runs spatial query and aspatial query simultaneously. The method uses a new sampling method that samples data having low probability used in query. Therefore proposed method improves spatial query accuracy and query processing speed as applying spatial filtering operation to sampling operator.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.3
• /
• pp.2158-2164
• /
• 2015

In u-GIS environments, various load shedding techniques have been researched in order to balance loads caused by input spatial data streams. However, typical load shedding methods on aspatial data lack regard for characteristics of spatial data, also previous load shedding approaches on spatial, which still lack regard for spatial data density or dynamic input data stream, give rise to troubles on spatial query processing performance and accuracy. Therefore, dynamic load shedding scheme over spatial data stream is proposed through stored spatial data deviation and load ratio of input data stream in order to improve spatial continuous query accuracy and performance in u-GIS environment. In proposed scheme, input data which are a big probability related to spatial continuous query may be a strong chance to be dropped relatively.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.06c
• /
• pp.193-195
• /
• 2006

인터넷 사용자의 급격한 증가와 기업들의 서비스 통합으로 다양한 시스템으로 구성된 온라인 웹 환경의 서비스가 제공되고 있다. 시간제한성의 서비스를 사용할 경우 예측하지 못한 부하발생으로 시스템의 폭주상태가 발생하게 된다. 예측하지 못한 부하에 대해 서비스 품질을 보장할 수 있는 부하제한 방법이 연구되었으나 웹 사용자의 사용패턴을 고려하지 못하고 있다. 본 논문에서는 폭주하는 서비스 상태에서 연계된 시스템 간 부하균형 상태를 유지하면서 사용자에게 동등한 만족도의 서비스 품질을 제공하는 방안을 제안하고 모의실험을 통해 서비스 성공률과 사용 평등성 비율을 분석하였다.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1707_1708
• /
• 2009

Unit master control(UMC)는 발전소의 요구 부하신호를 설정하는 최상위의 제어레벨이며 UMC의 설정값은 자동급전 지령신호(Automatic Dispatch System : ADS) 또는 운전원이 설정하는 값에 따라 보일러 및 터빈 Master에 Unit 요구 신호를 출력하여 하위제어 레벨인 공기, 연료, 급수 등을 조절할 수 있는 기기에 Unit 부하 요구 신호(Unit Load Demand : ULD)에 따라 제어 되도록 하는 방법으로서, Unit 목표부하 설정, Unit 목표부하 상/하한 제한, 목표부하 변화율 제한, 주파수 보정, Runback/Rundown/ Runup, 보일러 및 터빈 Demand 신호생성의 기능을 가지고 있다.

• Annual Conference of KIPS
• /
• 2009.04a
• /
• pp.340-343
• /
• 2009

u-GIS 환경에서 GeoSensor로부터 수집되는 시공간 데이터는 데이터 스트림의 특징을 포함한다. 데이터 스트림은 다양한 입력 속도로 끊임없이 입력되고, 데이터의 크기 또한 가변적이다. 이런 이유로 한정적인 메모리와 처리능력의 시스템은 과부하 현상이 발생한다. 이를 해결하기 위해 초과되는 데이터를 버려 메모리 초과를 방지하는 기법들이 연구되고 있다. 공간질의는 공간과 위치 값을 기반으로 이루어지는 연산으로 공간질의 정확도는 공간과 위치 정보를 통해 보장된다. 그러나 기존 기법인 랜덤부하제한 기법과 의미적부하제한 기법은 공간질의가 요구하는 공간과 위치 값에 대해 고려하지 않고 삭제하기 때문에 공간질의에 대한 정확도가 감소하는 문제를 갖는다. 본 논문에서는 공간의 이용도를 이용하여 차등적 비율을 적용한 부하제한 기법은 연구하였다. 이 기법은 등록된 공간질의의 영역 겹침 정도에 따라 중요 레벨을 증가시키고, 이를 토대로 시공간 데이터의 중요도를 파악하여 중요도마다 주어진 비율에 의하여 차등적으로 삭제한다. 결과적으로 기존 기법보다 다소 높은 Drop rate를 통해 질의 처리 속도를 빠르게 회복시켰으며, 중요 데이터를 최대한 유지하여 Error rate를 감소시켰다.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.1
• /
• pp.31-40
• /
• 2012

u-GIS DSMSs have been researched to deal with various sensor data from GeoSensors in ubiquitous environment. Also, they has been more important for high availability. The data from GeoSensors have some characteristics that increase explosively. This characteristic could lead memory overflow and data loss. To solve the problem, various load shedding methods have been researched. Traditional methods drop the overloaded tuples according to a particular criteria in a single server. Tuple deletion sensitive queries such as aggregation is hard to satisfy accuracy. In this paper a dual processing load shedding method is suggested to improve the accuracy of aggregation in clustering environment. In this method two nodes use replicated stream data for high availability. They process a stream in two nodes by using a characteristic they share stream data. Stream data are synchronized between them with a window as a unit. Then, processed results are merged. We gain improved query accuracy without data loss.

• Journal of Korea Multimedia Society
• /
• v.12 no.9
• /
• pp.1242-1251
• /
• 2009

A DSMS(Data Stream Management System) in ubiquitous environment processes huge data that input from a number of sensor. The existed system is used with a load shedding method that is eliminated with a part of huge data stream when it doesn't process the huge data stream. The Load shedding method has to filter a part of input data. This is because, data completeness or reliability is decreased. In this paper, we proposed the overload prediction load balancing to maintain data completeness when the system has an overload. The proposed method predicts the overload time. and than it is decreased with data loss when achieves the prediction overload time. The performance evaluation shows that the proposed method performs better than the existed method.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.2004-2005
• /
• 2007

고온 초전도체를 이용한 자속구속형 사고전류제한기는 1차권선과 2차권선을 감는 방향이나 감은 횟수의 비율에 따라서 부하전류용량과 전류제한용량이 다르다. 부하전류용량은 사고 발생 시 최초의 전류 제한 레벨과 밀접하게 관련이 되는데 자속구속형 사고전류제한기에서 최초의 전류 제한 레벨은 인덕턴스에 의해서 결정되기 때문이다. 전류제한용량은 사고전류제한기의 임피던스와 관계된다. 이 논문에서 자속구속형 사고전류제한기의 변압기 특성을 변화시키면서 부하전류용량과 전류제한용량의 변화를 살펴보았다.