• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.83-94
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• 2004

Recent researches which purport to Integrate distributed information have been concentrated on developing efficient mediator systems that not only provide a high degree of autonomy for local users but also support the flexible integration of required functions for global users. However, there has been little attention on how to evaluate a global query in a mediator. A global query is transformed into a set of its sub-queries and each sub-query is the unit of evaluation in a remote server. Therefore, it is possible to speed up the execution of a global query if the previous results of frequently evaluated sub-queries are materialized in a mediator. Since the Integration schema of a mediator can be incrementally modified and the evaluation frequency of a global query can also be continuously varied, query usage should be carefully monitored to determine the optimized set of materialized sub-queries. Furthermore, as the number of sub-queries increases, the optimization process itself may take too long, so that the optimized set Identified by a long optimization process nay become obsolete due to the recent change of query usage. This paper proposes the adaptive selection of materialized sub-queries such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a query from the past, the accumulated usage frequency of a query decays as time goes by.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.46-54
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• 2018

The Internet of Things (IoT) is an environment in which various devices provide services to users through communications. Because of the nature of the IoT, data are stored and distributed in heterogeneous information systems. In this situation, IoT end applications should be able to access data without having information on where the data are or what the type of storage is. This mechanism is called Service Discovery (SD). However, some problems arise, since the current SD architectures search for data in physical devices. First, turnaround time increases from searching for services based on physical location. Second, there is a need for a data structure to manage devices and services separately. These increase the administrator's service configuration complexity. As a result, the device-oriented SD structure is not suitable to the IoT. Therefore, we propose an SD structure called Name-based Service-centric Service Discovery (NSSD). NSSD provides name-based centralized SD and uses the IoT edge gateway as a cache server to speed up service discovery. Simulation results show that NSSD provides about twice the improvement in average turnaround time, compared to existing domain name system and distributed hash table SD architectures.

• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.47-56
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• 2005

Recently, with the rapid development of mobile computing, wireless positioning technologies, and the generalization of wireless internet, LBS (Location Based Service) which utilizes location information of moving objects is serving in many fields. In order to serve LBS efficiently, the location data server that periodically stores location data of moving objects is required. Formerly, GIS servers have been used to store location data of moving objects. However, GIS servers are not suitable to store location data of moving objects because it was designed to store static data. Therefore, in this paper, we designed and implemented an extended SLDS(Short-term Location Data Subsystem) for real-time Location Based Services. The extended SLDS is extended from the SLDS which is a subsystem of the GALIS(Gracefully Aging Location Information System) architecture that was proposed as a cluster-based distributed computing system architecture for managing location data of moving objects. The extended SLDS guarantees real-time service capabilities using the TMO(Time-triggered Message-triggered Object) programming scheme and efficiently manages large volume of location data through distributing moving object data over multiple nodes. The extended SLDS also has a little search and update overhead because of managing location data in main memory. In addition, we proved that the extended SLDS stores location data and performs load distribution more efficiently than the original SLDS through the performance evaluation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1206-1218
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• 1992

Token ring systems which control to switch the data stream of networks by passing the token have been widely used to medium access controls in many ring or bus topology LANs. The system could be modeled for analysis as single-server-multi-queue system of the cyclic service method. These concepts could be expanded to multi-token ring systems interconnected with single ring consisting of bridges implemented simply to be stored and transmitted. In the proposal for the performance analysis of the interconnected token ring system, in has been assumed M/G/1 queueing model that frame arrivals are the Poisson process at each station queue and frame sizes are independently and identically distributed. And the average time delays were analyzed mathematically for arbitrary frame transferred from source station to destination area. The time delay of the frame transmission could be explained as the sum of the average time which the token passed from arbitrary position to source station, such as the waiting time in the source station transferring the previous arrival frames, and the propagation time from source station to interdestinated point. These delays were given as the sum of the duration from inner and outer bridge queues, the time delays from inner and outer bridge queues, and the time from outer bridge queue to destination station. These results were investigated by varing parameters effected to total time delays. In the results, those factors to be effected to dominant the total time delays were increased were in the cases of the high arrival rates and the high ration of destination of the other outerring. The system were shown the time delays increased exponentially in spite of the priority service policy. In order to decreasing the number of outerrings and increasing the number of nodes in backbone relatively, so the systems could be decreased the total delay in the interconnected token ring system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.2
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• pp.36-42
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• 2011

The current healthcare information systems field to meet the growing demand for healthcare for a variety of building systems and operation, and subsequent information on the budget continues to increase, but the current system, although the association link between the various systems made does not, with organizations with information about each of the standardization and real-time network status data do not consist of various materials, such as insufficient to provide real-time issues have been raised. This paper proposes a Integrated information system on Healthcare based on JXTA to solve problems mentioned above. Until now, in a network environment for data storage and management is the most widely used server-intensive structure, while an increase in users and traffic difficulties in data management and communications services to handle the growing number of servers increase faster than information associated with the cost savings, P2P model in terms of efficient data management has emerged as a new solution. Therefore this paper designs a platform for Integrated information system on Healthcare based on JXTA as a method to integrate health information data and services, and then proves that the new information system on healthcare based on JXTA is the suitable model.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.50-58
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• 2017

Recently, some methods of converging heterogeneous fire sensor data have been proposed for effective fire detection, but the rule-based methods have low adaptability and accuracy, and the fuzzy inference methods suffer from detection speed and accuracy by lack of consideration for images. In addition, a few image-based deep learning methods were researched, but it was too difficult to rapidly recognize the fire event in absence of cameras or out of scope of a camera in practical situations. In this paper, we propose a novel fire detection system combining a deep learning algorithm based on CNN and fuzzy inference engine based on heterogeneous fire sensor data including temperature, humidity, gas, and smoke density. we show it is possible for the proposed system to rapidly detect fire by utilizing images and to decide fire in a reliable way by utilizing multi-sensor data. Also, we apply distributed computing architecture to fire detection algorithm in order to avoid concentration of computing power on a server and to enhance scalability as a result. Finally, we prove the performance of the system through two experiments by means of NIST's fire dynamics simulator in both cases of an explosively spreading fire and a gradually growing fire.

• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.22-32
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• 2008

To overcome the weakness of the image retrieval system using the existing Ontology and the distributed image based on the database having a simple structure, HERMES was suggested to ensure the self-control of various image suppliers and support the image retrieval based on semantic, the mentioned framework could not solve the problems which are not considered the deterioration in the capacity and scalability when many users connect to broker server simultaneously. In this paper the tables are written which in the case numerous users connect at the same time to the supply analogous level of services without the deterioration in the capacity installs Broker servers and then measures the performance time of each inner Broker Component through Monitoring System and saved and decides the ranking in saved data. As many Query performances are dispersed into several Servers User inputted from the users Interface with reference to Broker Ranking Table, Load Balancing system improving reliability in capacity is proposed. Through the experiment, the scheduling technique has proved that this schedule is faster than existing techniques.

• The KIPS Transactions:PartA
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• v.19A no.1
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• pp.1-8
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• 2012

Network-based intelligent robot is connected with network system, provides interactions with humans, and carries out its own roles on ubiquitous computing environments. URC (Ubiquitous Robot Companion) robot has been proposed to develop network-based robot by applying distributed computing techniques. On URC robot, it is possible to save the computing power of robot client by environments, has been proposed to develop robot software using service-oriented architecture on server-client computing environments. The SOMAR client robot consists of two layers - device service layer and robot service layer. The device service controls physical devices, and the robot service abstracts robot's services, which are newly defined and generated by combining many device services. RSEL (Robot Service Executing Language) is defined in this paper to represent relations and connections between device services and robot services. A RESL document, including robot services by combining several device services, is translated to a programming language for robot client system using RSEL translator, then the translated source program is compiled and uploaded to robot client system with RPC (Remote Procedure Call) command. A SOMAR client system is easy to be applied to embedded systems of host/target architecture. Moreover it is possible to produce a light-weight URC client robot by reducing workload of RSEL processing engine.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.9
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• pp.209-216
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• 2019

Publish-subscribe communication model is popular for various type of distributed applications because of its loosely coupled style connections. Among the various architecture style for publish-subscribe system, peer-to-peer architecture has been used for the mission critical application domain since it provides high scalability and real-timeness. On the other hand, to utilize the bandwidth of given networks, message filtering is frequently used to reduce the number of messages on the system. Even if P2P provides superior scalability, it is hard to apply filtering to the its messaging system because the filtering process should be done on the peer-side in P2P architecture that are usually done on the broker server in conventional pub/sub architecture. In this paper, we propose a hierarchical subscription management structure as well as message forwarding scheme for efficient data dissemination. Our proposed scheme reduces the number of received messages by filter-out un-wanted messages and offloading the message dissemination work to other subscribers to enhance the messaging throughput.

• Convergence Security Journal
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• v.18 no.1
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• pp.19-31
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• 2018

As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.