• ETRI Journal
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• v.21 no.4
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• pp.23-28
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• 1999

In this paper, we analyze the performance benefits of broadband ATM networks when the call control and management flows are separated from user data flows. The virtual path tunneling concept for control and management flows are applied to the same physical ATM networks. The behaviors of channel throughput and transfer delay are analyzed. It results that the proposed virtual short-cut paths can maintain the network being stable with acceptable bandwidth. They are very useful to provide the stable control and management capabilities for Internet and mobile applications in the broadband ATM networks. In our numerical results, the effective throughputs of the proposed virtual shout-ut channel are about three times than those of end-to-end user data channels with hop distances of 10, and about two times than those with hop distance of 5 when the link blocking probability increases to 0.1. It concludes that the effective channel bandwidth are greatly reduced down while physical links are not stable and user traffic flows are occasionally overflowed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1169-1176
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• 2000

In this paper, label assignment schemes considering the IP flow model for the efficient MPLS traffic engineering are proposed and evaluated. Based on the IP flow model, the IP flows are classified into transient flows and base flows. Base flows, which last for a long time, transmit data in high bit rate, and be composed of many packets, have good implications for the MPLS traffic engineering, because they usually cause network congestion. To make use of base flows for the MPLS traffic engineering, we propose two base flow classifiers and label assignment schemes where transient flows are allocated to the default LSPs and base flows to explicit LSPs. Proposed schemes are based on the traffic-driven label triggering method combined with a routing tabel. The first base flow classifier uses both flow size in packet counts and routing entries, and the other one, extending the dynamic X/Y flow classifier, is based on a cut-through ratio. Proposed schemes are shown to minimize the number of labels, not degrading the total cut-through ratio.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3320-3331
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• 1999

In this paper, we explore two ways to improve the bandwidth assurance performance of Assured Service(AS). It is well known that AS fails to meet the bandwidth assurance target for large-profile TCP flows competing with many small-profile flows. This flows after the back-offs induced by packet drops. Thus currently proposed solution to this problem naturally focus on modifying TCP's behavior to counter the unfairness in the TCP dynamics. Unfortunately, these proposals lack practicability in terms of the required changes in the incumbent Internet infrastructure. Admitting this difficulty, we instead look to not yet deployed Diff-Serv mechanisms for practical solutions. In particular, we investigate the role of RIO, RED with IN(in-profile) and OUT(out-profile), queue management scheme in the assurance failure for As. Specifically, we identify the inadequacy of RIO that aggravates the bandwidth assurance failure. Then we alleviates the bandwidth assurance failure problem by separately controlling the out-of-profile packet queue length. Through extensive simulations we demonstrate that RI+O extends the regime where AS consistently provides the bandwidth assurance.

• Journal of computational fluids engineering
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• v.19 no.2
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• pp.8-16
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• 2014

Two-dimensional prediction capability of several analysis codes, such as XFOIL, MSES, and KFLOW, is compared and analyzed based on computational results of airfoil flows. To this end the transition transport equations are coupled with the Navier-Stokes equations for the prediction of the natural transition and the separation-induced transition. Experimental data of aerodynamic coefficients are used for comparison with numerical results for the transitional flows. Numerical predictions using the transition transport model show a good agreement with experimental data. Discrepancies have been found in the prediction of the pressure drag are mainly caused by the difference in the far-field circulation correction methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6A
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• pp.910-917
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• 2000

Because the random early detection(RED) algorithm deals all flows with the same best-effort traffic characteristic, it can not correctly control the output link bandwidth for the flows with different traffic characteristics. To remedy this problem, several per-flow algorithms have been proposed. In this paper, we propose a new per-flow type Fair Droptail algorithm which can fairly allocate bandwidth among flows over a shared output link. By evenly allocating buffers per flow, the Fair Droptail can restrict a flow not to use more bandwidth than others. In addition, it can be simply implemented even if it employs the per-flow state mechanism, because the Fair Droptail only keeps each information of flow in active state.

• Management & Information Systems Review
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• v.34 no.5
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• pp.213-231
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• 2015

In this paper, I examine whether the listed companies in Korea tend to manage operating cash flows upward via classification shifting after the adoption of K-IFRS. As proxies for cash flow management, I derive a measure of abnormal operating cash flows borrowing from Lee(2012). Alternative proxies include a series of categorical variables designed to identify the types of classification shifting of interest and dividend payments among others, in the statement of cash flows. Higher level of estimated abnormal operating cash flows, and the classification of interest/dividend payments in non-operating activity sections are considered to indicate the managerial intention to maximize reported operating cash flows. I consider several potential incentives to manage operating cash flows, which include financial distress, the credit rating proximity to investment/non-investment cutoff threshold, avoidance of negative or decreasing operating cash flows relative to previous period and so forth. In a series of empirical analyses, I do not find evidence in support of the opportunistic classification shifting explanation, inconsistent with several previous literature in Korea. In contrast, I observe negative associations between the CFO management proxies and selected incentives, which suggest that the classification is likely to represent above average cash flow performance rather than opportunistic motives exercised to maximize reported operating cash flows. I reckon that this observation is, in part, driven by the K-IFRS requirement to maintain temporal consistency in classifying interest and dividend receipts/payments in cash flow statement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Agricultural Extension & Community Development
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• v.27 no.3
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• pp.125-134
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• 2020

The regional centrality plays a very important role in national and regional planning and it is measured by data such as people, goods, and information flows among regions. The inter-regional flows are usually considered by only direct flows, yet indirect flows, which are generated accordingly from direct flows, are not critically considered. Most centrality studies have also hardly reflected the indirect flow in the network analysis. This study demonstrates the significance of the indirect flows to enhance accuracy of the regional centrality. The nationwide dataset of inter-regional commuter traffic matrix is used in this study and analysed into two groups; one to consider only direct flow and the other both direct and indirect flows. The results indicate remarkable differences of centrality raking between two groups such as Yeongam of Jeonnam Province(+60th), Eumseong of Chungbuk Province(+57th), Gwacheon of Gyeonggi Province (-35th), and Nowon of Seoul (-32nd). It clearly shows the significant influence of indirect flow for regional centrality study. This also reveals regional centrality ranking in Korea by considering direct and indirect flows of commuters. Jung, Gangnam, and Jongno of Seoul are categorized in the highest rank group and Ulleung of Gyeongbuk, Ongjin of Incheon, and Jindo of Jeonnam are in the lowest group. The top group includes seven districts of Seoul, two of Busan, and one of Gyeonggi Province. The bottom group includes mostly island and costal areas. As this study shows an accurate method of centrality measurement, it has a significant implication to lead an effective regional planning.

• Journal of Korean Library and Information Science Society
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• v.31 no.2
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• pp.113-138
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• 2000

This article deals with a sensitive issue on intella-tual freedom in Korean society. In details, the authors introduce the current laws Inhibiting Sree flows of information in korean society, and analyze the fundamental problems including in such laws or sections of tllc laws with various examples. Nso introduced are various efforts by the legal circle and NGOs for the improvement of the current situation, with an analysis of the limitatio and problems in such efforts. Finally, the authors suggest the 'desirable' strategies and methods for correcting or abolishmg the current 'controversial' laws which are serious barriers against free information flows, particularly emphasizing the responsibility of librarians who have to be gatekeepers of knowledge and infonnation in a svcalled information society.

• Management & Information Systems Review
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• v.28 no.3
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• pp.69-98
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• 2009

This study investigates in-sample and out-of-sample predictive abilities of accruals and accruals components with respect to future cash flows using models developed by Barth et al.(2001). In tests, data collected fromda62 Korean KOSPI and KOSDAQ listed firms for ccr4-2007 are used. Results of in-sample prediction tests are similar with those of Barth et al.(2001). Their accrual components model is better than other three models(NI only model, CF only model and NI-total accruals model) in future cash flows predictive ability. That is, in the case of in-sample prediction, accrual components excluding amortization have additional information contents for future cash flows. But in out-of-sample tests, the results are different. The model including operational cash flows(CF only model) shows best out-of-sample predictive ability with respect to future cash flows among above four prediction models. The accrual components model of Barth et al.(2001) has worst out-of-sample predictive ability. The results are robust to sensitivity analyses. In conclusion, we can't find the evidence that accruals and accrual components have predictive ability with respect to future cash flows in out-of-sample prediction tests. This results are consistent with results of Lev et al.(2005), and inconsistent with the belief of accounting standards formulating organizations such as FASB and KASB.