• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.194-203
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• 2008

Construction companies require management system to increase efficiency and profit because of receiving competition and globalizing business environment. Since 1990s, construction companies have made various attempts to innovate business structure both internally and externally by means of BPR, 6 Sigma, PI, and Workflow. Some improvements were made, but most of them were temporary, and insufficient to provide the much-needed promptness of business process in responding to the changes. Furthermore, the recent methods of applying BPM and practical using are limited to the theory and method of other industries, and also the attempts of applying BPM in construction industry are at the stage of theoretical approaching and examining in a few construction companies. Accordingly, this study deduces the necessity of adopting BPM based on change of business paradigm for construction companies and limits of current researches, failure causes and problems of application attempts of BPM and process management. And also, we analyze Advance of BPM and suggest the application method of business process management model for construction companies.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.9_10
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• pp.485-496
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• 2008

As the complexity of SoC (System-on-Chip) design increases dramatically. traditional system performance analysis and verification methods based on RTL (Register Transfer Level) are no more valid for increasing time-to-market pressure. Therefore a new design methodology is desperately required for system verification in early design stages. and hardware software (HW-SW) cosimulation at TLM (Transaction Level Modeling) level has been researched widely for solving this problem. However, most of HW-SW cosimulators support few restricted ion levels only, which makes it difficult to integrate HW-SW cosimulators with different ion levels. To overcome this difficulty, this paper proposes a multipurpose framework for HW SW cosimulation to provide systematic SoC design flow starting from software application design. It supports various design techniques flexibly for each design step, and various HW-SW cosimulators. Since a platform design is possible independently of ion levels and description languages, it allows us to generate simulation models with various ion levels. We verified the proposed framework to model a commercial SoC platform based on an ARM9 processor. It was also proved that this framework could be used for the performance optimization of an MJPEG example up to 44% successfully.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2B
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• pp.279-288
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• 2004

Rapidly emerging P2P(Peer to Peer) applications generate very bursty traffic, which gives a lot of burden to network, and the amount of such traffic is increasing rapidly. Thus it is becoming more important to understand the characteristics of such traffic and reflect it when we design and analyze the network. To do that we measured the traffic in a campus network and present flow statistics and traffic models of the measured traffic, and compare them with those of the web traffic. The results indicate that P2P traffic is much burstier than web traffic and as a result it negatively affects network performance. We modeled P2P traffic using self-similar traffic model to predict packet delay and loss occurred in network which are very important to evaluate network performance. We also predict queue length distribution and loss probability in SSQ(Single Sewer Queue). To assess accuracy of traffic model, we compare the SSQ statistics of traffic models with that of the traffic trace. The results show that self-similar traffic models we use can predict P2P traffic behavior in network precisely. It is expected that the traffic models we derived can be used when we design network capacity and predict network performance and QoS of the P2P applications.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.5
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• pp.37-45
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• 2004

As Internet technologies are mature, many new applications that are different characteristics are emerging. Recently we see wide use of P2P(Peer to Peer) applications of which traffic shows different statistical characteristics compared with traditional application such as web(HTTP) and FTP(File Transfer Protocol). In this paper, we measured subscriber network of KT(Korea Telecom) to analyze P2P traffic characteristics. We show flow characteristics of measured traffic. We also estimate Hurst parameter of P2P traffic and compare self-similarity with web traffic. Analysis results indicate that P2P traffic is much bustier than web traffic and makes both upstream traffic and downstream traffic be symmetric. To predict parameters related QoS such as packet loss and delays we model P2P traffic using two self-similar traffic models and predict both loss probability and mm delay then compare their accuracies. With simulation we show that the self-similar traffic models we derive predict the performance of P2P traffic accurately and thus when we design a network or evaluate its performance, we can use the P2P traffic model as reference input traffic.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.309-319
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• 2014

Virtual Network service is a key characteristics of future Internet which is debate internationally. There are two kinds of network virtualization technologies considered lately: network functions virtualization and virtual network approaches. Several national wide research networks including US's GENI project have experimented technologies for future Internet and in particular network virtualization is one of key issues. Representative Korean research network, KREONET, is working on deploying virtual network framework as a preliminary for future Ineternet using the virtualization model of SDN/OpenFlow which is typical network model of future Internet. This paper proposes a stepwise model to bring virtual network services in KREONET. Firstly, we requirements of KREONET users' virtual network service and network resource management and network deploying virtual network. Finally, we verify the adequacy of our virtual network model for KREONET.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.165-171
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• 2019

The study of the computer architecture has shown that major improvements in price-to-energy performance stems from domain-specific hardware development. This paper analyzes the tensor processing unit (TPU) ASIC which can accelerate the reasoning of the artificial neural network (NN). The core device of the TPU is a MAC matrix multiplier capable of high-speed operation and software-managed on-chip memory. The execution model of the TPU can meet the reaction time requirements of the artificial neural network better than the existing CPU and the GPU execution models, with the small area and the low power consumption even though it has many MAC and large memory. Utilizing the TPU for the tensor flow benchmark framework, it can achieve higher performance and better power efficiency than the CPU or CPU. In this paper, we analyze TPU, simulate the Python modeled OpenTPU, and synthesize the matrix multiplication unit, which is the key hardware.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.672-682
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• 2020

The Korea Nowadays, which is research on digital twin technology for efficient operation in various industrial/manufacturing sites, is being actively conducted, and gradual depletion of fossil fuels and environmental pollution issues require new renewable/eco-friendly power generation methods, such as wave power plants. In wave power generation, however, which generates electricity from the energy of waves, it is very important to understand and predict the amount of power generation and operational efficiency factors, such as breakdown, because these are closely related by wave energy with high variability. Therefore, it is necessary to derive a meaningful correlation between highly volatile data, such as wave height data and sensor data in an oscillating water column (OWC) chamber. Secondly, the methodological study, which can predict the desired information, should be conducted by learning the prediction situation with the extracted data based on the derived correlation. This study designed a workflow-based training model using a machine learning framework to predict the pressure of the OWC. In addition, the validity of the pressure prediction analysis was verified through a verification and evaluation dataset using an IoT sensor data to enable smart operation and maintenance with the digital twin of the wave generation system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1509-1521
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• 2011

WfMC, which is one of the international standardization organizations leading the business process and workflow technologies, has been officially released the BPAF1.0 that is a standard format to record process instances' event logs according as the business process intelligence mining technologies have recently issued in the business process and workflow literature. The business process mining technologies consist of two groups of algorithms and their analysis techniques; one is to rediscover flow-oriented process-intelligence, such as control-flow, data-flow, role-flow, and actor-flow intelligence, from process instances' event logs, and the other has something to do with rediscovering relation-oriented process-intelligence like process-driven social networks and process-driven affiliation networks from the event logs. The current standardized format of BPAF1.0 aims at only supporting the control-flow oriented process-intelligence mining techniques, and so it is unable to properly support the relation-oriented process-intelligence mining techniques. Therefore, this paper tries to extend the BPAF1.0 so as to reasonably support the relation-oriented process-intelligence mining techniques, and the extended BPAF is termed BPAF2.0. Particularly, we have a plan to standardize the extended BPAF2.0 as not only the national standard specifications through the e-Business project group of TTA, but also the international standard specifications of WfMC.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.301-315
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• 2010

Recently, competition between companies has intensified and so has the necessity of creating a new business value inventions has increased. A numbers of Business organizations are beginning to realize the importance of business process management. Processes however can often not go the way they were initially designed or non-efficient performance process model could be designed. This can be due to a lack of cooperation and understanding between business analysts and system developers. To solve this problem, business process mining which can be used as the basis of the business process re-engineering has been recognized to an important concept. Current process mining research has only focused their attention on extracting workflow-based process model from competed process logs. Thus there have a limitations in expressing various forms of business processes. The disadvantage in this method is process discovering time and log scanning time in itself take a considerable amount of time. This is due to the re-scanning of the process logs with each new update. In this paper, we will presents a modified FP-Tree algorithm for FP-Tree based business processes, which are used for association analysis in data mining. Our modified algorithm supports the discovery of the appropriate level of process model according to the user's need without re-scanning the entire process logs during updated.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.279-290
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• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.