• Journal of Communications and Networks
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• v.16 no.5
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• pp.534-547
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• 2014

Large-scale failures resulting from natural disasters or intentional attacks are now causing serious concerns for communication network infrastructure, as the impact of large-scale network connection disruptions may cause significant costs for service providers and subscribers. In this paper, we propose a new framework for the analysis and prevention of network service disruptions in large-scale failure scenarios. We build dynamic deterministic and probabilistic models to capture the impact of regional failures as they evolve with time. A probabilistic failure model is proposed based on wave energy behaviour. Then, we develop a novel approach for preventive protection of the network in such probabilistic large-scale failure scenarios. We show that our method significantly improves uninterrupted delivery of data in the network and reduces service disruption times in large-scale regional failure scenarios.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.21-33
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• 2007

An overlay network is a virtual network which is constructed on top of a physical computer network. A node in the overlay network is connected through virtual or logical links, where each link corresponds to a path of the links in the underlying physical network. Overlay networks are suitable for sharing heterogeneous resources in distributed environments, However, overlay networks are limited for achieving reliable communication that failure detection in overlay networks is a very important issue. In this paper, we review conditions of conventional failure detection and propose a new approach to failure detection and resilience which can be applied to HRing (Hierarchical Ring) overlay networks. The proposed method consists of the failure detection and the failure resilience phases. Because it utilizes the characteristics of the HRing overlay network for failure detection, it can reduce unnecessary network traffic and provide better scalability and flexibility. We also analyzed and evaluated the performance of the proposed approach through simulations.

• The Journal of Internal Korean Medicine
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• v.44 no.3
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• pp.313-353
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• 2023

Objectives: Heart failure is a chronic disease with increasing prevalence rates despite advancements in medical technology. Korean medicine utilizes herbal prescriptions to treat heart failure, but little is known about the specific herbal medicines comprising the network of herbal prescriptions for heart failure. This study proposes a novel methodology that can efficiently develop prescriptions and facilitate experimental research on heart failure by utilizing existing databases. Methods: Herbal medicine prescriptions for heart failure were identified through a PubMed search and compiled into a Google Sheet database. NetMiner 4 was used for network analysis, and the individual networks were classified according to the herbal medicine classification system to identify trends. K-HERB NETWORK was utilized to derive related prescriptions. Results: Network analysis of heart failure prescriptions and herbal medicines using NetMiner 4 produced 16 individual networks. Uhwangcheongsim-won (牛黃淸心元), Gamiondam-tang (加味溫膽湯), Bangpungtongseong-san (防風通聖散), and Bunsimgi-eum (分心氣飮) were identified as prescriptions with high similarity in the entire network. A total of 16 individual networks utilized K-HERB NETWORK to present prescriptions that were most similar to existing prescriptions. The results provide 1) an indication of existing prescriptions with potential for use to treat heart failure and 2) a basis for developing new prescriptions for heart failure treatment. Conclusion: The proposed methodology presents an efficient approach to developing new heart failure prescriptions and facilitating experimental research. This study highlights the potential of network pharmacology methodology and its possible applications in other diseases. Further studies on network pharmacology methodology are recommended.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.30-37
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• 1995

The mechanical seals, which are installed in rotating machines like pump and compressor, are gengrally used as sealing devices in the many fields of industries. The failure of mechanical seals such as leakage,fast and severe wear, excessive torque, and squeaking results in big problems. To monitor the failure of mechanical seals and to propose the proper monitoring techniques with artificial neural network, sliding wear experiments were conducted. Torque and temperature of the mechanical seals were measured during experiments. Optical microstructure was observed for the wear processing after every 10 minute sliding at rotation speed of 1750 rpm and scanning electron microscopy was also observed. During the experiment, the variation of torque and temperature that meant an abnormal phenomenon, was observed. That experimental data recorded were applied to the developed monitoring system with artificial neural network. This study concludes that torque and temperature of mechanical seals wil be used to identify and to monitor the condition of sliding motion of mechanical seals. An availability to monitor the mechanical seal failure with artificial neural network was confirmed.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.319-335
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• 2012

In this study, we design an applicable model enabling internet protocol television (IPTV) service providers to use a virtual network (VN) for IPTV service delivery. The model addresses the guaranteed service delivery, cost effectiveness, flexible control, and scalable network infrastructure limitations of backbone or IP overlay-based content networks. There are two major challenges involved in this research: i) The design of an efficient, cost effective, and reliable virtual network topology (VNT) for IPTV service delivery and the handling of a VN allocation failure by infrastructure providers (InPs) and ii) the proper approach to reduce the cost of VNT recontruction and reallocation caused by VNT allocation failure. Therefore, in this study, we design a more reliable virtual network topology for solving a single virtual node, virtual link, or video server failure. We develop a novel optimization objective and an efficient VN construction algorithm for building the proposed topology. In addition, we address the VN allocation failure problem by proposing VNT decomposition and reconstruction algorithms. Various simulations are conducted to verify the effectiveness of the proposed VNT, as well as that of the associated construction, decomposition, and reconstruction algorithms in terms of reliability and efficiency. The simulation results are compared with the findings of existing works, and an improvement in performance is observed.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.500-504
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• 1995

A neural network based upon the back propagation algorithm was designed and applied to acoustic power spectra of electrohydraulic total artificial hearts in order to diagnose mechanical failure of devices. The trained network distinguished spectra of the mechanically damaged device from those of the undamaged device with overall success rate of 63%. Moreover, the network correctly classified more than 70% of spectra in the frequency bands of 0-100 Hz and 700-950 Hz. Consequently, the neural network analysis was useful for the diagnosis of mechanical failure of a total artificial heart.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.11-20
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• 2012

In a marine ubiquitous sensor network (USN) system using expensive sensors in the harsh ocean environment, it is very important to discover failures and devise recovery techniques to deal with such failures. Therefore, in order to perform failure modeling, this study analyzes the USN-based real-time water quality monitoring service of the Gaduri Aqua Farms at Songdo Island of Yeosu, South Korea and devises methods of discovery and recovery of failure by classifying the types of failure into system element failure, communication failure, and data failure. In particular, to solve problems from the perspective of data, this study defines data integrity and data consistency for use in identifying data failure. This study, by identifying the exact type of failure through analysis of the cause of failure, proposes criteria for performing relevant recovery. In addition, the experiments have been made to suggest the duration as to how long the data should be stored in the gateway when such a data failure occurs.

• Smart Structures and Systems
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• v.33 no.6
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• pp.465-482
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• 2024

In this paper, a robust wireless sensor network configuration design method is proposed to develop the optimal configuration under the consideration of sensor failure and energy consumption. A malfunctioned sensor in a wireless sensor network may lead to data transmission failure of the entire sensing cluster, inducing severe deterioration in system identification performance. The proposed method determines a wireless sensor network configuration that is robust against sensor failure. By utilizing Bayesian inference, we introduce a robust indicator to evaluate the impact on estimation accuracy of sensor configurations with various malfunctioned sensors. Moreover, a network formation strategy is proposed to optimize the energy efficiency of the wireless sensor network configuration. Therefore, the resultant robust wireless sensor network configuration can operate with the minimum energy consumption while the measurement information of the sensor network with malfunctioned sensors can be guaranteed. The proposed method is illustrated by designing the robust wireless sensor network configurations of a truss model and a bridge model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5200-5222
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• 2017

The separation of control plane and data plane in Software Defined Network (SDN) makes it flexible to control the network behavior, while also causes some inconveniences to the link failure recovery due to the delay between fail point and the controller. To avoid delay and packet loss, pre-defined backup paths are used to reroute the disrupted flows when failure occurs. However, it may introduce large overhead to build and maintain these backup paths and is hard to dynamically construct backup paths according to the network status so as to avoid congestion during rerouting process. In order to realize congestion aware fast link failure recovery, this paper proposes a novel method which installs multi backup paths for every link via source routing and per-hop-tags and spread flows into different paths at fail point to avoid congestion. We carry out experiments and simulations to evaluate the performance of the method and the results demonstrate that our method can achieve congestion aware fast link failure recovery in SDN with a very low overhead.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.65-73
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• 2004

The capability to provide the network service must survive even if a significant network system element is disrupted. To sustain the network service under the system failure, network survivability mechanisms minimizing the impact of failures are needed. Also, since the mobile network has its unique characteristic, the survivability scheme for the vulnerability of the mobile network is required. This paper proposes a survivability scheme to support the reliable service of the wireless access point level (BS-base station system). By the survivability scheme, the mobile network can use an overlap BS of the cellular network architecture after a BS system failure. We analyze the performance of the proposed scheme using Markov model. Also, a computer simulation is used for the scheme analysis. The proposed scheme shows that the service of the mobile network can be provided under the BS system failure.