• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.100-105
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• 2020

With the advent of the 5G era, the rapid growth in demand for mobile content services has increased the need for additional backhaul investment. To meet this demand, employing a content delivery network (CDN) and optical access solution near the last mile has become essential for the configuration of 5G networks. In this paper, a cache-enabled architecture using the passive optical network (PON) is presented to serve video on demand (VoD) for users. For efficient use of mobile backhaul, I propose a request deduplication scheme (RDS) that can provide all the requested services missed in cache with minimum bandwidth by eliminating duplicate requests for movies within tolerable range of the quality of service (QoS). The performance of the proposed architecture is compared with and without RDS in terms of the number of requests arriving at the origin server (OS), hit ratio, and improvement ratio according to user requests and cache sizes.

• Journal of Information Technology Applications and Management
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• v.10 no.2
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• pp.61-71
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• 2003

Ad-hoc networks are characterized by multi-hop wireless links, frequently changing network topology and the need for efficient dynamic routing protocols. In an Ad-hoc network, each host assumes the role of a router and relays packets toward final destinations Because a packet is broadcast to all neighboring nodes, the optimality criteria of wireless network routing is different from that of wired network routing. tn this paper 1 point out the more important cost factor than the number of links in the Ad-hoc network. A class routing protocols called on-demand protocols has recently found attention because of their low routing overhead since it performs a blind flooding to look for a path. In this paper, 1 propose the method which reduces overhead by using the information of neighboring nodes and doing a selective flooding. Simulation results demonstrate better reduction of routing overheads with this scheme.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.287-289
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• 2009

The conventional computing is a centralizing system, but it has been gradually going to develop ubiquitous computing which moves roles away from the main. The Community Computing, a new paradigm, is proposed to implement environment of ubiquitous computing. In this environment, it is important to accept the user demand. Hence in this paper recognizes pattern of user's activity statistically and proposes a method of pattern estimation in community computing. In addition, user's activity varies with time and the activity has the priority We reflect these. Also, we improve accuracy of the method through Knowledge Base organization and the feedback system. We make program using Microsoft Visual C++ for evaluating performance of proposed method, then simulate it. We can confirm it from the experiment result that using proposal method is better in environment of community computing.

• IE interfaces
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• v.18 no.3
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• pp.343-349
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• 2005

This study presents the empirical results of comparing several demand forecasting methods for Supply Chain Management(SCM). Adaptive exponential smoothing using change detection statistics (Jun) is compared with Trigg and Leach's adaptive methods and SAS time series forecasting systems using weekly SCM demand data. The results show that Jun's method is superior to others in terms of one-step-ahead forecast error and eight-step-ahead forecast error. Based on the results, we conclude that the forecasting performance of SCM solution can be improved by the proposed adaptive forecasting method.

• Earthquakes and Structures
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• v.4 no.5
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• pp.527-555
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• 2013

This paper proposes probabilistic models for estimating the seismic demands on reinforced concrete (RC) bridges with base isolation. The models consider the shear and deformation demands on the bridge columns and the deformation demand on the isolation devices. An experimental design is used to generate a population of bridges based on the AASHTO LRFD Bridge Design Specifications (AASHTO 2007) and the Caltrans' Seismic Design Criteria (Caltrans 1999). Ground motion records are used for time history analysis of each bridge to develop probabilistic models that are practical and are able to account for the uncertainties and biases in the current, common deterministic model. As application of the developed probabilistic models, a simple method is provided to determine the fragility of bridges. This work facilitates the reliability-based design for this type of bridges and contributes to the transition from limit state design to performance-based design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2840-2853
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• 2015

A major challenge in network service providers is to provide adequate resources in service level agreements based on forecasts of future demands. In this paper, we address the problem of capacity provisioning in a network subject to demand uncertainty such that a network coded multicast is applied as the data delivery mechanism with limited budget to purchase extra capacity. We address some particular type of uncertainty sets that obtain a tractable constrained capacity provisioning problem. For this reason, we first formulate a mathematical model for the problem under uncertain demand. Then, a robust optimization model is proposed for the problem to optimize the worst-case system performance. The robustness and effectiveness of the developed model are demonstrated by numerical results. The robust solution achieves more than 10% reduction and is better than the deterministic solution in the worst case.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.371-374
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• 2004

The ultimate purpose of Supply Chain Management (SCM) is maximizing the profits of the overall Supply Chain (SC) through increasing customer satisfaction and decreasing operating cost. It can be successfully accomplished only when SC system balances demands with supply activities coordinated by aggregate planning, mid-term level of Supply Chain Planning(SCP). However, the existing measures to mainly estimate the specific function of SCM are not enough to evaluate the state of SC with respect to the balance between supply and demand in operating. To solve this problem, we develop a new SC performance measure, Balancing Point, using momentum concept. a fundamental knowledge of physics. Momentum concept can explain the relation among objects so that it can consider the balance between supply and demand in SC operating. The developed measure can not only consider the current state of the SC system but also take planned but not executed supply activities and upcoming demands into account. Therefore, using Balancing point, we can be aware of the unbalanced state of SC in advance.

• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.139-150
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• 2006

The aim of this study is to establish an efficient distribution planning for a capacitated multi-stage supply chain. We assume that the demand information during planning horizon is given a deterministic form using a certain forecasting method. Under such a condition, we present a cost effective heuristic method for minimizing chain-wide supply chain inventory cost that is the sum of holding and backorder costs by using look-ahead technique. We cope with the capacity restriction constraints through look-ahead technique that considers not only the current demand information but also future demand information. To evaluate performance of the proposed heuristic method, we compared it with the extant research that utilizes echelon stock concept, under various supply chain settings.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.225-235
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• 1986

Dataflow computers exhibit a high degree of parallelism which can not be obtained easily with the conventional von-Neumann architecture. Since many instructions are ready for execution simultaneously, concurrency can easily by achieved by the multiple processors modified the data-flow machine. In paper, we describe an improved dataflow architecture which is designed by adding the demand propagation network to the MIT dataflow machine. and show the improved performance by the execution time and the efficiency of processing elements through simulation with the time acceleration method.

• Journal of English Language & Literature
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• v.57 no.6
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• pp.911-938
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• 2011

The present study examined the effect of two variables of task complexity, reasoning demand and time pressure, each from the resourcedirecting and resource-dispersing dimension in Robinson's (2001) framework of task classification. Reasoning demand was operationalized as the two types of texts to read and summarize, expository and argumentative. Time pressure was operationalized as the two modes of performance, oral and written. Six university students summarized the two types of text orally and twenty four students from the same school summarized them in the written form. Results from t test and ANCOVA showed that in the oral mode, reasoning demand tends to heighten the complexity of the language used in the summary in competition with accuracy but such an effect disappeared in the written mode. It was interpreted that the degree of time pressure is not the only difference between the oral and written modes but that the two modes may be fundamentally different cognitive tasks, and that Robinson's (2001) and Skehan's (1998) models were differentially supported by the oral mode of tasks but not by the written mode of the tasks.