• ETRI Journal
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• v.39 no.2
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• pp.222-233
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• 2017

Debugging in distributed environments, such as wireless sensor networks (WSNs), which consist of sensor nodes with limited resources, is an iterative and occasionally laborious process for programmers. In sensor networks, it is not easy to find unintended bugs that arise during development and deployment, and that are due to a lack of visibility into the nodes and a dearth of effective debugging tools. Most sensor network debugging tools are not provided with effective facilities such as real-time tracing, remote debugging, or a GUI environment. In this paper, we present a hybrid debugging framework (HDF) that works on WSNs. This framework supports query-based monitoring and real-time tracing on sensor nodes. The monitoring supports commands to manage/control the deployed nodes, and provides new debug commands. To do so, we devised a debugging device called a Docking Debug-Box (D2-Box), and two program agents. In addition, we provide a scalable node monitor to enable all deployed nodes for viewing. To transmit and collect their data or information reliably, all nodes are connected using a scalable node monitor applied through the Internet. Therefore, the suggested framework in theory does not increase the network traffic for debugging on WSNs, and the traffic complexity is nearly O(1).

• Journal of Information Processing Systems
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• v.5 no.2
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• pp.77-86
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• 2009

In this paper, we propose a framework for the real-time monitoring of wireless biosensors. This is a scalable platform that requires minimum human interaction during set-up and monitoring. Its main components include a biosensor, a smart gateway to automatically set up the body area network, a mechanism for delivering data to an Internet monitoring server, and automatic data collection, profiling and feature extraction from bio-potentials. Such a system could increase the quality of life and significantly lower healthcare costs for everyone in general, and for the elderly and those with disabilities in particular.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.901-923
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• 2017

Efficient key distribution and management mechanisms as well as lightweight ciphers are the main pillar for establishing secure wireless sensor networks (WSN). Several symmetric based key distribution protocols are already proposed, but most of them are not scalable, yet vulnerable to a small number of compromised nodes. In this paper, we propose an efficient and scalable key management and distribution framework, named KMMR, for large scale WSNs. The KMMR contributions are three fold. First, it performs lightweight local processes orchestrated into upward and downward tiers. Second, it limits the impact of compromised nodes to only local links. Third, KMMR performs efficient secure node addition and revocation. The security analysis shows that KMMR withstands several known attacks. We implemented KMMR using the NesC language and experimented on Telosb motes. Performance evaluation using the TOSSIM simulator shows that KMMR is scalable, provides an excellent key connectivity and allows a good resilience, yet it ensures both forward and backward secrecy. For a WSN comprising 961 sensor nodes monitoring a 60 hectares agriculture field, KMMR requires around 2.5 seconds to distribute all necessary keys, and attains a key connectivity above 96% and a resilience approaching 100%. Quantitative comparisons to earlier work show that KMMR is more efficient in terms of computational complexity, required storage space and communication overhead.

• ETRI Journal
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• v.30 no.2
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• pp.205-215
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• 2008

Many control schemes have been proposed for flow-level traffic control. However, flow-level traffic control is implemented only in limited areas such as traffic monitoring and traffic control at edge nodes. No clear solution for end-to-end architecture has been proposed. Scalability and the lack of a business model are major problems for deploying end-to-end flow-level control architecture. This paper introduces an end-to-end transport architecture and a scalable control mechanism to support the various flow-level QoS requests from applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.86-109
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• 2019

Cloud computing systems' performance is still a central focus of research for determining optimal resource utilization. Running several existing benchmarks simultaneously serves to acquire performance information from specific cloud system resources. However, the complexity of monitoring the existing performance of computing systems is a challenge requiring an efficient and interactive user directing performance-monitoring system. In this paper, we propose an effective multivariate control framework for monitoring cloud systems performance. The proposed framework utilizes the hardware cloud systems performance metrics, collects and displays the performance measurements in terms of meaningful graphics, stores the graphical information in a database, and provides the data on-demand without requiring a third party software. We present performance metrics in terms of CPU usage, RAM availability, number of cloud active machines, and number of running processes on the selected machines that can be monitored at a high control level by either using a cloud service customer or a cloud service provider. The experimental results show that the proposed framework is reliable, scalable, precise, and thus outperforming its counterparts in the field of monitoring cloud performance.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.559-565
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• 2005

In this paper, we propose a stereoscopic video coding scheme for subway accident monitoring system. The proposed designed for providing flexible video among various displays, such ass control center, station employees and train driver. We uses MPEG-2 standard for coding the left-view sequence and IBMDC coding scheme 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. The experimental results show the efficiency of proposed coding scheme by comparison with already known methods and the advantages of disparity estimation in terms of scalability overhead. 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.65-68
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• 2018

오늘날 네트워크 서비스에 대한 수요가 증가함에 따라 네트워크 트래픽 또한 증가하고 있다. 이는 네트워크 서비스 구성을 복잡하게 만들어 최종 사용자에게 전달되는 네트워크 기능의 동적 구성이 요구된다. Service Function Chaining (SFC)은 일련의 Service Function (SF) 세트로 구성된 새로운 네트워크 서비스 배포 모델이다. SFC는 특정 서비스에 따라 플로우를 분류하여 네트워크 운영자의 효율적인 서비스 제공을 보장한다. SFC의 성능은 SFC를 구성하는 SF Instance (SFI)와 상관 관계를 가진다. 이때 다수의 SFC 환경에서 단일의 SFI 사용 시, 트래픽 오버플로우가 발생할 수 있다. 따라서, 본 논문에서는 확장 가능한 SFC 프로비저닝을 위한 Monitoring as a Service (MaaS)를 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.317-320
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• 2009

At the present day, the use of containers crisscrossing seven seas and intercontinental transport has significantly increased and bringing the change on the shape of the world economy which we cannot be neglected. Additionally, with the recent technological advances in wireless sensor network (WSN) technologies, has providing an economically feasible monitoring solution to diverse application that allow us to envision the intelligent containers represent the next evolutionary development step in order to increase the efficiency, productivity, utilities, security and safe of containerized cargo shipping. This paper we present a comprehensive containerized cargo monitoring system which has adaptively embedded WSN technology into cargo logistic technology. We share the basic requirement for an autonomous logistic network that could provide optimum performance and a suite of algorithms for self-organization and bi-directional communication of a scalable large number of sensor node apply on container regardless inland and maritime transportation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2256-2262
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• 2010

The requirements for automated handing of business process and its monitoring usually have a proprietary form for each enterprise. Unlike the conventional database transaction, business process takes long time for its completion and incorporates very complex handling logics along with business situations. Since those handling logics are frequently changing in accordance with the business policies or environment, enterprises want to integrally capture the whole business semantics while monitoring those process instances. In this paper, we adopted GMA(Grid Monitoring Architecture) for the integrated monitoring of business processes. The GMA(Grid Monitoring Architecture) is a very scalable architecture to effectively monitor and manage monitoring information under the heterogeneous environment. By introducing complex event handling features into GMA to support various processing logics, we could implement a system that enables automated execution and high-level monitoring of business processes.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.95-100
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• 2022

Cloud computing platform is a shared pool of resources and services with various kind of models delivered to the customers through the Internet. The methods include an on-demand dynamically-scalable form charged using a pay-per-use model. The main problem with this model is the allocation of resource in dynamic. In this paper, we have proposed a mechanism to optimize the resource provisioning task by reducing the job completion time while, minimizing the associated cost. We present the Cooperative Agents Dynamic Resource Allocation and Monitoring in Cloud Computing CADRAM system, which includes more than one agent in order to manage and observe resource provided by the service provider while considering the Clients' quality of service (QoS) requirements as defined in the service-level agreement (SLA). Moreover, CADRAM contains a new Virtual Machine (VM) selection algorithm called the Node Failure Discovery (NFD) algorithm. The performance of the CADRAM system is evaluated using the CloudSim tool. The results illustrated that CADRAM system increases resource utilization and decreases power consumption while avoiding SLA violations.