• Journal of KIISE:Databases
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• 제33권2호
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• pp.163-174
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• 2006

In distributed wireless sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. We propose a classification framework for continuous multivariate stream data. The proposed approach works in two steps. In the preprocessing step, it takes input as a sliding window of multivariate stream data and discretizes the data in the window into a string of symbols that characterize the signal changes. In the classification step, it uses a standard text classification algorithm to classify the discretized data in the window. We evaluated both supervised and unsupervised classification algorithms. For supervised, we tested Bayesian classifier and SVM, and for unsupervised, we tested Jaccard, TFIDF Jaro and Jaro Winkler. In our experiments, SVM and TFIDF outperformed other classification methods. In particular, we observed that classification accuracy is improved when the correlation of attributes is also considered along with the n-gram tokens of symbols.

• Journal of Korea Spatial Information System Society
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• 제9권3호
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• pp.35-50
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• 2007

In a data centric sensor network, a sensor node to store data is determined by the measured data value of each sensor node. Therefore, if the same data occur frequently, the energy of the sensor node to store the data is exhausted quickly due to the concentration of loads. And if the sensor network is extended, the communication cost for storing data and processing queries is increased, since the length of the routing path for them is usually in the distance. However, the existing researches that generally focus on the efficient management of data storing can not solve these problems efficiently. In this paper, we propose a NUNS(Non-Uniform Network Split) method that can distribute loads of sensor nodes and decrease the communication cost caused by the sensor network extension. By dividing the sensor network into non-uniform partitions that have the minimum difference in the number of sensor nodes and the splitted area size and storing the data which is occurred in a partition at the sensor nodes within the partition, the NUNS can distribute loads of sensor nodes and decrease the communication cost efficiently. In addition, by dividing each partition into non-uniform zones that have the minimum difference in the splitted area size as many as the number of the sensor nodes in the partition and allocating each of them as the processing area of each sensor node, the NUNS can protect a specific sensor node from the load concentration and decrease the unnecessary routing cost.

• Journal of KIISE:Software and Applications
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• 제32권6호
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• pp.554-569
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• 2005

In the semistructured distributed documents, it is very difficult to formalize and implement the query processing system due to the lack of structure and rule of the data. In order to precisely retrieve and process the heterogeneous semistructured documents, it is required to handle multiple mappings such as 1:1, 1:W and W:1 on an element simultaneously and to generate the schema from the distributed documents. In this paper, we have proposed an query processing algorithm for querying and answering on the heterogeneous semistructured data or documents over distributed systems and implemented with a metadata interface. The algorithm for generating local queries from the global query consists of mapping between g1oba1 and local nodes, data transformation according to the mapping types, path substitution, and resolving the heterogeneity among nodes on a global input query with metadata information. The mapping, transformation, and path substitution algorithms between the global schema and the local schemas have been implemented the metadata interface called DBXMI (for Distributed Documents XML Metadata Interface). The nodes with the same node name and different mapping or meanings is resolved by automatically extracting node identification information from the local schema automatically. The system uses Quilt as its XML query language. An experiment testing is reported over 3 different OEM model semistructured restaurant documents. The prototype system is developed under Windows system with Java and JavaCC compiler.

• Review of KIISC
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• 제4권1호
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• pp.7-19
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• 1994

• Proceedings of the Korean Operations and Management Science Society Conference
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• 한국경영과학회 1994년도 추계학술발표회 발표논문집; 연세대학교경영관, 서울; 8 Oct. 1994
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• pp.141-141
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• 1994

• Journal of KIISE:Computing Practices and Letters
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• 제13권5호
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• pp.282-292
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• 2007

In this paper, we propose the active model based on the distributed object group framework which provides adaptive information sharing service to support it to various Healthcare home service. And we applied it to Healthcare home service. This proposed model provides information that collected from physical environment of the home network and sensors for healthcare service according to situation of the user. We uses information of the healthcare information database which was constructed previously, and we uses TMO scheme for to solve each other different periodic qualify. We uses information of the healthcare information database which was constructed previously, and we uses TMO scheme for to solve each other different periodic quality. Specialty, We wrote about interaction of various Healthcare Home services for adaptive information services, and wrote about u-healthcare framework based on DOGF. Finally, we apply active model to healthcare monitoring service, and we showed its result and performance evaluation.

• The Transactions of the Korea Information Processing Society
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• 제2권5호
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• pp.645-654
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• 1995

A distributed DBMS integrates local schemas that are independently designed, maintained, and managed by different users at each site providing a global virtual schema. This global schema supports users at a specific site to transparently utilize local database at different sites. The security features of the local schema should also not be changed in the global schema integrating security features of each local schema. Researches on the integration of security features into local schema in distributed DBMS environment, however, are very rate. This pater using the multilevel secure object-oriented database model(as the model for the definition of a local schema in distributed environment) which is an extension of the object-oriented models. It also suggests eight integration methods that can maintain the security features of local schemas. The eight methods are classified by the object classes and by relationships among them.

• Journal of KIISE:Computer Systems and Theory
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• 제27권2호
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• pp.188-199
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• 2000

This paper presents an efficient stable logging scheme for the distributed shared memory system based on the lazy release consistent memory model. In the proposed scheme, inter-process dependency is traced and stable logging is performed when the dependency relation between processes actually happens. With the dependency tracking, the proposed scheme requires much less frequency of stable logging, comparing with the previous schemes in which stable logging is performed whenever any information transfer happens between processes. Also, in the proposed scheme, every data item accessed by a process is not logged, but only the access information is logged in the stable storage. For the recovery from a failure, the correct version of the accessed data items can be effectively traced by using the logged access information. As a result, the amount of logged information is also reduced.

• Journal of KIISE:Databases
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• 제32권6호
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• pp.616-627
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• 2005

In the shared storage file system, systems can directly access the shared storage device through specialized data-only subnetwork unlike in the network attached file server system. In this shared-storage architecture, data consistency is maintained by some designated set of lock servers which use control network to send and receive the lock information. Furthermore, lease mechanism is introduced to cope with the control network failure. But when the control network is partitioned, participating systems can no longer make progress after the lease term expires until the network recovers. This paper addresses this limitation and proposes a method that allows partitioned systems to make progress under the partition of control network. The proposed method works in a manner that each participating system is rotationally given a predefined lease term periodically. It is also shown that the proposed mechanism always preserves data consistency.

• Journal of KIISE:Computer Systems and Theory
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• 제26권7호
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• pp.752-765
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• 1999

대부분 병렬처리 시스템에서 성능 파라미터는 복잡하고 프로그램의 수행 시 예견할 수 없게 변하기 때문에 컴파일러가 프로그램 수행에 대한 최적의 성능 파라미터들을 컴파일 시에 결정하기가 힘들다. 본 논문은 병렬 처리 시스템의 프로그램 수행 시, 변화하는 시스템 성능 상태에 따라 전체 성능이 최적화로 적응하는 적응 수행 방식을 제안한다. 본 논문에서는 이 적응 수행 방식 중에 적응 프로그램 수행을 위한 이론적인 방법론 및 구현 방법에 대해 제안하고 적응 제어 수행을 위해 프로그램의 데이타 공유 단위에 대한 적응방식(적응 입도 방식)을 사용한다. 적응 프로그램 수행 방식은 프로그램 수행 시 하드웨어와 컴파일러의 도움으로 프로그램 자신이 최적의 성능을 얻을 수 있도록 적응하는 방식이다. 적응 제어 수행을 위해 수행 시에 병렬 분산 공유 메모리 시스템에서 프로세서 간 공유될 수 있은 데이타의 공유 상태에 따라 공유 데이타의 크기를 변화시키는 적응 입도 방식을 적용했다. 적응 입도 방식은 기존의 공유 메모리 시스템의 공유 데이타 단위의 통신 방식에 대단위 데이타의 전송 방식을 사용자의 입장에 투명하게 통합한 방식이다. 시뮬레이션 결과에 의하면 적응 입도 방식에 의해서 하드웨어 분산 공유 메모리 시스템보다 43%까지 성능이 개선되었다. Abstract On parallel machines, in which performance parameters change dynamically in complex and unpredictable ways, it is difficult for compilers to predict the optimal values of the parameters at compile time. Furthermore, these optimal values may change as the program executes. This paper addresses this problem by proposing adaptive execution that makes the program or control execution adapt in response to changes in machine conditions. Adaptive program execution makes it possible for programs to adapt themselves through the collaboration of the hardware and the compiler. For adaptive control execution, we applied the adaptive scheme to the granularity of sharing adaptive granularity. Adaptive granularity is a communication scheme that effectively and transparently integrates bulk transfer into the shared memory paradigm, with a varying granularity depending on the sharing behavior. Simulation results show that adaptive granularity improves performance up to 43% over the hardware implementation of distributed shared memory systems.