• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.71-77
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• 2015

This paper suggested dynamic application framework based data collecting and monitoring technique using wireless sensor network. The development of application for wireless measurement node firmware program integrates with various sensors and performs control. Collecting data of the user application is downloaded from the node onboard process wirelessly. In addition, the user application can change the temperature initial value of the nodes, which enables dynamic sampling of the measurement nodes. Therefore, dynamic sampling control of the nodes can reduce the power consumptions of sensors compared to existing wired data monitoring.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.217-225
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• 2014

Analysis of social media such as Twitter can yield interesting perspectives to understanding human behavior, detecting hot issues, identifying influential people, or discovering a group and community. However, it is difficult to gather the data relevant to specific topics due to the main characteristics of social media data; data is large, noisy, and dynamic. This paper proposes a new algorithm that dynamically selects the seed nodes to efficiently collect tweets relevant to topics. The algorithm utilizes attributes of users to evaluate the user influence, and dynamically selects the seed nodes during the collection process. We evaluate the proposed algorithm with real tweet data, and get satisfactory performance results.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.441-450
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• 2002

As the size of embedded system software increase bigger and bigger, and it's complexity is grower and grower, the usage of dynamic memory management scheme such collector also has been increased. Using the garbage collector, however, inherently lead us performance degradation. In order to resolve this kind of performance problem in the Java based embedded system. we introduce an explicit dynamic memory free method to the automated dynamic memory management environment. which can be performed by a programmer. In the worst case, the prosed scheme shows the same performance as the case of that only garbage collector is working, since the unclaimed garbage objects will eventually be collected later by the garbage collector. In the best case. our method is free from any runtime overhead because the applications can be implemented without any intervention of the garbage collector. Although the proposed method can be facilitated with all the existing garbage collection algorithms, it shows an outperform in the case of mark-and-sweep algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.254-257
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• 2007

정보기술의 발달로 정보를 수집, 관리, 공유하기가 용이해 짐에 따라 여러 조직이나 기관에서는 개인정보를 수집해 관리하고 있다. 수집한 개인정보를 통계나 연구 등을 목적으로 배포할 때 개인의 프라이버시를 보호하기 위해 k-anonymity 와 l-diversity 원리가 제안되었고 이를 기반으로 하는 프라이버시 보호 기법들이 제안되었다. 그러나 기존 방법들은 정적인 데이터를 단 한번 배포하는 것을 가정하기 때문에 지속적으로 데이터에 삽입이나 삭제가 발생하는 동적 데이터 환경에 그대로 적용하기 적합하지 않다. 본 논문에서는 동적 데이터 환경에서 l-diversity 을 유지하면서 데이터 삽입과 삭제를 효율적으로 처리할 수 있는 기법을 제안한다. 제안 기법은 일반화를 사용하지 않기 때문에 일반화에서 발생하는 정보의 손실이 발생하지 않고 삽입과 삭제의 처리가 간단한 것이 특징이다.

• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.756-761
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• 2015

With the emergence of the Internet-of-Things (IoT) paradigm, there is a growing demand for personalized services using IoT contexts acquired from heterogeneous IoT devices. However, due to the mismatch between IoT context exchange schemes of context-aware services and IoT devices, IoT applications can acquire IoT contexts only from IoT devices that support the same IoT context exchange schemes. In this paper, we propose dynamic methods to mediate those mismatches on the IoT context exchange schemes. With the proposed mediation methods, context-aware services can collect IoT contexts from heterogeneous IoT devices without considering their IoT context exchange schemes.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.9-18
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• 2013

In recent years, the demands of multimedia data in wireless sensor networks have been significantly increased for the high-quality environment monitoring applications that utilize sensor nodes to collect multimedia data. However, since the amount of multimedia data is very large, the network lifetime and network performance are significantly reduced due to excessive energy consumption on particular nodes. In this paper, we propose an energy-efficient dynamic area compression scheme in wireless multimedia sensor networks. The proposed scheme minimizes the energy consumption in the huge multimedia data transmission process by compression using the Chinese Remainder Theorem(CRT) and dynamic area detection and division algorithm. Our experimental results show that our proposed scheme improves the data compression ratio by about 37% and reduces the amount of transmitted data by about 56% over the existing scheme on average. In addition, the proposed scheme increases network lifetime by about 14% over the existing scheme on average.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.57-69
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• 2005

The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using real-time traffic data collected from Freeway Traffic Management System (FTMS). In existing research, the micro-simulation models had been used to get a link distribution proportion by time process. Because of hi-level problem between the traffic flow model and the optimal OD solution algorithm, it is difficult for the existing models to be loaded at FTMS. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a genetic algorithm. The proposed methodology is evaluated by using the real-time data of SOHAEAN freeway, South Korea.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.125-136
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• 2005

The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using VDS and AVI data. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a kalman filter algorithm. The proposed dynamic OD estimation model use ilk and off-ramp volumes collected from VDS and partial OD collected from AVI data to raise the accuracy of dynamic OD estimation. The proposed model is evaluated by using the real-time data of SOHAEAN freeway, South Korea. The result of the proposed dynamic OD estimation model based on VDS and AVI data is better than that of based on VDS data. The more AVI systems are equipped at on and off-ramp, the more excellent result of estimation accuracy is expected.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.30-39
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• 2013

Web crawler should maintain fresh data with minimum server overhead for large amount of data in the web sites. The overhead in the server increases rapidly as the amount of data is exploding as in the big data era. The amount of web information is increasing rapidly with advanced wireless networks and emergence of diverse smart devices. Furthermore, the information is continuously being produced and updated in anywhere and anytime by means of easy web platforms, and smart devices. Now, it is becoming a hot issue how frequently updated web data has to be refreshed in data collection and integration. In this paper, we propose dynamic web-data crawling methods, which include sensitive checking of web site changes, and dynamic retrieving of web pages from target web sites based on historical update patterns. Furthermore, we implemented a Java-based web crawling application and compared efficiency between conventional static approaches and our dynamic one. Our experiment results showed 46.2% overhead benefits with more fresh data compared to the static crawling methods.

• Journal of KIISE:Information Networking
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• v.35 no.4
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• pp.318-325
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• 2008

Most of the sensor applications collect and analyze sensor data within a given period of time. When sensor send a data to sink, it spend many communication cost. Accordingly, a compression algorithm is one of the most critical issues for the communication cost decrease in sensor fields. In this paper, we propose an algorithm for compressing sensor data using the dynamic bit assignment technique. In our algorithm, sink collect sensor data within a short period of time and make bit assign information. Then sink send the information to sensor. Finally, sensors compresssensing data and send to sink.