• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.55-60
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• 2009

Race conditions in current Java programs must be detected because it may cause unexpected result by non-deterministic executions. For detecting such races during program execution, execution flows of all threads and all access events can be monitored. It is difficult for previous race detection techniques to monitor all threads and access events in actuality because these techniques analyze the files traced during program execution or modify original source programs and then monitor these programs. This paper presents a transparent scalable monitoring tool to detect races using JDI(Java Debug Interface) where JDI is 100% pure java interface to provide in JDPA(Java Platform Debugger Architecture) and is able to provide information corresponding to events occurred in run-time of programs. This tool thus can monitor execution flows of all threads and all access events without program modification. We prove transparency of the presented tool and grasp the efficiency of it using a set of published benchmark programs. As a result of this, the suggested tool can monitor all threads and accesses of these programs without their modification, and their monitoring time is increased to more than 20 times.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.269-281
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• 2011

STEPSTONE is a joint industry-university project to create open source technology that would enable the scalable, "friction-free" integration of device-based healthcare solutions into enterprise systems using a Service Oriented Architecture (SOA). Specifically, STEPSTONE defines a first proposal to a Service Oriented Device Architecture (SODA) framework, and provides for initial reference implementations. STEPSTONE also intends to encourage a broad community effort to further develop the framework and its implementations. In this paper, we present SODA, along with two implementation proposals of SODA's device integration. We demonstrate the ease by which SODA was used to develop an end-to-end personal healthcare monitoring system. We also demonstrate the ease by which the STEPSTONE system was extended by other participants - Washington State University - to include additional devices and end user interfaces. We show clearly how SODA and therefore SODA devices make integration almost automatic, replicable, and scalable. This allows telehealth system developers to focus their energy and attention on the system functionality and other important issues, such as usability, privacy, persuasion and outcome assessment studies.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.818-825
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• 2016

Network management and anomaly detection are challenges in high-speed networks due to the high volume of packets that has to be analysed. Flow-based analysis is a scalable method which reduces the high volume of network traffic by dividing it into flows. As sampling methods are extensively used in flow generators such as NetFlow, the impact of sampling on the performance of flow-based analysis needs to be investigated. Monitoring using sampled traffic is a well-studied research area, however, the impact of sampling on flow-based anomaly detection is a poorly researched area. This paper investigates flow sampling methods and shows that these methods have negative impact on flow-based anomaly detection. Therefore, we propose an efficient probabilistic flow sampling method that can preserve flow traffic distribution. The proposed sampling method takes into account two flow features: Destination IP address and octet. The destination IP addresses are sampled based on the number of received bytes. Our method provides efficient sampled traffic which has the required traffic features for both flow-based anomaly detection and monitoring. The proposed sampling method is evaluated using a number of generated flow-based datasets. The results show improvement in preserved malicious flows.

• Journal of Convergence Society for SMB
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• v.2 no.1
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• pp.41-50
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• 2012

In this research, we developed a scalable resource monitoring system for large scale scientific computing data centers. Usually, there are limitations and overheads for keeping track of every computing nodes because of the huge number of computing nodes. So, this research proposes a layered summarizing techniques during collection of all system resource information. The technique results in improved scalability by reducing the amount of information at higher layer. Our prototype system which is implemented with web service is applicable with the HTML5 mobile web technology on smart devices.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.484-486
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• 2005

Passenger safety is a primary concern of railway system but, it has been urgent issue that dozens of people are killed every year when they falloff from train platforms. Recently, advancements in IT have enabled applying vision sensors to railway environments, such as CCTV and stereo camera sensors. In this paper, we propose a stereoscopic video coding scheme for subway accident monitoring system. The proposed scheme is designed for providing flexible video among various displays, such as control center, station employees and train driver. We uses MPEG-2 standard for coding the left-view sequence and IBMDC for predicting the P- and B-types of frames of the right-view sequence. IBMDC predicts matching block by interpolating both motion and disparity predicted macroblocks. To provide efficient stereoscopic video service. we define both temporally and spatially scalable layers for each eye's-view by using the concept of Spatio-Temporal scalability. According to the experimental results. we expect the proposed functionalities will play a key role in establishing highly flexible stereoscopic video codec for ubiquitous display environment where devices and network connections are heterogeneous.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1362-1376
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• 2016

A cloud computing system can be characterized by the provision of resources in the form of services to third parties on a leased, usage-based basis, as well as the private infrastructures maintained and utilized by individual organizations. To attain the desired reliability and energy efficiency in a cloud data center, trade-offs need to be carried out between system performance and power consumption. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. The work presented in this paper is directed towards the development of an Energy-efficient and Performance-aware Cloud System equipped with strategies for dynamic switching of optimization approach. Moreover, a platform is also provided for the deployment of a Wind Farm CMS (Condition Monitoring System) which allows ubiquitous access. Due to the geographically-dispersed nature of wind farms, the CMS can take advantage of the cloud's highly scalable architecture in order to keep a reliable and efficient operation capable of handling multiple simultaneous users and huge amount of monitoring data. Using the proposed cloud architecture, a Wind Farm CMS is deployed in a virtual platform to monitor and evaluate the aging conditions of the turbine's major components in concurrent, yet isolated working environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.493-502
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• 2010

In this paper we propose a scalable sensor network system that makes mesh network among the sink nodes to solve the scalability problem of existing sensor network which is caused by multi-hop networking between the sensor nodes. In the proposed system, the sink nodes have the wireless networking ability to communicate with another sink nodes in mesh fashion, and with the monitoring nodes which is located in the local area or internet area. Especially, the system includes L4(Application Layer) routing mechanism that provides subscribe/publish service to serve selective transmission of sensor data to the specific monitoring nodes. The collected sensor data is transmitted to the monitoring nodes when the sensor data is matched with the monitoring node's interesting value.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.605-614
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• 2009

Despite its graceful bandwidth saving nature, IP multicast has not been successful in widely spreading and using. Challenging includes policy and technological issues such as inter-domain routing, multicast availability and reachability. Properly detecting and isolating the faults would be the first step to stabilize IP multicast. In this paper, we introduce a scalable multicast monitoring framework. To efficiently cope with multicast network and networking problems, it enlarges its monitoring scopes from collecting delivery statistics to verifying end-to-end multicast availability, reachability and interactivity. We carry out various networking experiments to verify the scalability and feasibility of the proposed framework.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.915-922
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• 2003

The Grid is an infrastructure to connect heterogeneous resources that are scattered over areas with high-speed network and to cooperate with each other. To support Grid applications, network resources should be managed, since the network has to be safe and reliable. The Grid Monitoring Architecture Working Group (GMAWG) of the Global Grid Forum (GGF) proposed an effective architecture to be scalable across wide-area networks and encompass a large number of heterogeneous resources. In this paper, we describe the design and implementation of Grid network monitoring system based on the GMA for practical network management. By this system, network operations center can form a management system flexibly and scalably for Grid network.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.423-438
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• 2010

Wireless smart sensors enable new approaches to improve structural health monitoring (SHM) practices through the use of distributed data processing. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While much of the technology associated with smart sensors has been available for nearly a decade, there have been limited numbers of fulls-cale implementations due to the lack of critical hardware and software elements. This research develops a flexible wireless smart sensor framework for full-scale, autonomous SHM that integrates the necessary software and hardware while addressing key implementation requirements. The Imote2 smart sensor platform is employed, providing the computation and communication resources that support demanding sensor network applications such as SHM of civil infrastructure. A multi-metric Imote2 sensor board with onboard signal processing specifically designed for SHM applications has been designed and validated. The framework software is based on a service-oriented architecture that is modular, reusable and extensible, thus allowing engineers to more readily realize the potential of smart sensor technology. Flexible network management software combines a sleep/wake cycle for enhanced power efficiency with threshold detection for triggering network wide operations such as synchronized sensing or decentralized modal analysis. The framework developed in this research has been validated on a full-scale a cable-stayed bridge in South Korea.