• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.491-508
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• 2010

In peer-to-peer (P2P) on-demand streaming networks, the alleviation of server load depends on reciprocal stream sharing among peers. In general, on-demand video services enable clients to watch videos from beginning to end. As long as clients are able to buffer the initial part of the video they are watching, on-demand service can provide access to the video to the next clients who request to watch it. Therefore, the key challenge is how to keep the initial part of a video in a peer's buffer for as long as possible, and thus maximize the availability of a video for stream relay. In addition, to address the issues of delivering data on lossy network and providing scalable quality of services for clients, the adoption of multiple description coding (MDC) has been proven as a feasible resolution by much research work. In this paper, we propose a novel caching scheme for P2P on-demand streaming, called Dynamic Buffering. The proposed Dynamic Buffering relies on the feature of MDC to gradually reduce the number of cached descriptions held in a client's buffers, once the buffer is full. Preserving as many initial parts of descriptions in the buffer as possible, instead of losing them all at one time, effectively extends peers’ service time. In addition, this study proposes a description distribution balancing scheme to further improve the use of resources. Simulation experiments show that Dynamic Buffering can make efficient use of cache space, reduce server bandwidth consumption, and increase the number of peers being served.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1092-1099
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• 2017

In this paper, we propose a novel geographical on-demand routing protocol for a mobile ad-hoc network (MANET) that resolves the broadcast storm problem of ad-hoc on-demand distance vector (AODV) routing protocol. The candidates relaying route request (RREQ) packet are geographically restricted by the locations of the destination and a (RREQ sender. Then, the duplicate RREQs, which are generally discarded in the protocols that follow the principle of the AODV, are parsed to avoid redundant RREQ rebroadcasts and to perform passive acknowledgement with respect to a RREQ rebroadcast. The proposed routing protocol is implemented by modifying the source code of the AODV in QualNet. It is shown through QualNet simulations that the proposed routing protocol significantly improves the packet delivery ratio and the latency of the AODV in high-density and heavy traffic network scenarios.

• Journal of Korean Society of Rural Planning
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• v.16 no.3
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• pp.77-85
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• 2010

The objective of this study is to analyze demands and important level of rural amenity resources information in rural development consulting. For this study, the questionnaire survey was implemented to regional development consulting companies and organizations with three parts. The first part is about the methodologies in using for the rural development consulting, particularly, the collect processes of the amenity resources information and methods to establish development strategy are included in the questionnaire. In second part, essential factors for constructing the information system of rural amenity resources are investigated. Finally, the rural development project types were classified, and performed an analysis of important level for the rural amenity resources utilizing AHP technique. According to results of this study survey, the demands from residents are the most important factor for establishing rural development plan, and the relationship among neighboring regions and the amounts of rural amenity resources are also considered as important factors. The most important rural amenity resources are different as rural development project types.

• Journal of Intelligence and Information Systems
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• v.3 no.1
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• pp.31-45
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• 1997

To date, research on data mining has focused primarily on individual techniques to su, pp.rt knowledge discovery. However, the integration of elementary learning techniques offers a promising strategy for challenging a, pp.ications such as forecasting nonlinear processes. This paper explores the utility of an integrated a, pp.oach which utilizes a second-order learning process. The a, pp.oach is compared against individual techniques relating to a neural network, case based reasoning, and induction. In the interest of concreteness, the concepts are presented through a case study involving the prediction of network traffic for video-on-demand.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.29-39
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• 2019

In this study, we introduce a model that satisfies energy efficiency and economical efficiency by introducing and demonstrating cogeneration generators in industrial complexes using various actual data collected at the site. The proposed model is composed of three scenarios, ie, full - time operation, scenario operated according to demand, and a fusion type. In this study, the power generation profit and surplus thermal energy are measured according to the operation of the generator, and the thermal energy is traded according to the demand of the customer to calculate the profit and loss including the heat and evaluate the economic efficiency. As a result of the study, it is relatively profitable to reduce the generation of the generator under the condition that the electricity rate is low and the gas rate is high, while the basic charge is not increased. On the contrary, if the electricity rate is high and the gas rate is low, The more you start up, the more profit you can see. These results show that even a cogeneration power plant with a low economic efficiency due to a low "spark spread" has sufficient economic value if it can sell more than a certain amount of heat energy from a nearby customer and adjust the applied power through peak management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4207-4222
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• 2016

In a P2P (Peer-to-Peer) VoD (video-on-Demand) streaming system, the nodes' load is an important factor which affects the system performance. In the system, some nodes may receive too many requests, which leads to overload. On the other hand, some other nodes may receive too few requests, which leads to low utilization. Therefore, designing a reasonable load balancing strategy is important. However, existing related studies cannot handle this problem effectively, because they don't have an efficient dynamic load information management mechanism, and they don't distinguish the difference of requests when transfer the nodes' load. In this paper, to manage the dynamic load information efficiently, we design a load management table for each node. Based on the load information, we propose a load balancing strategy which uses a request migration algorithm (LBRM). Through simulations, our scheme can handle the load imbalance problem effectively and improve the users' playback fluency.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.105-119
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• 2015

The overseas expansion is essential to expand domestic geospatial industries in a state of saturation. But current overseas expansion method has be limited to expand global market. Inter-industry convergence strategies may be the most resonable alternative to expand global market through raising the expansion possibility to developing countries with ODA funds and to developed countries with converging global competitive industries. This research investigates various foreign developed and developing countries to draw each demand. As a result, easiness of convergence, confidentiality of information, complementarity of poor infrastructure, responsiveness of various demands and sustainability of system are needed to successful convergence on multiple industries. This research seeks convergence framework to meet this demands, and suggests each component. This convergence framework is consisted of geospatial convergence common framework, inter-industry convergence model and institutional supporting system for overseas expansion.

• Spatial Information Research
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• v.20 no.6
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• pp.77-90
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• 2012

In this paper, we examined how to utilize QR codes for meeting the information demand and making better use of the paper map. By Decision Tree Analysis, we investigated whether to have any intention to use the paper map with QR codes for receiving more information and what decision variables affect the answers. Thus, we also surveyed the area of providing information and sectoral demand for deriving additional information demand to being provided through QR codes. In the results of our study, we confirmed that the decision variables, to make any intention to use the paper map with QR code, are the frequency of using the paper, the experience of using the paper map, the intention to buy the paper map, the experience of using QR codes and the experience of buying the paper map. In these variables, the frequency of using the paper map is a major factor to decide whether it is intended to use the paper map with QR codes. we also identified that there are various additional information demand using the paper map with QR codes in the area of 'Daily life', 'Real estate', 'Education', 'Travel and Leisure', and 'Entertainment'. Especially additional information demand is high in the area of 'Travel and Leisure'. These results could be used to find a way how to vitalize the usage of paper map by introduction of QR codes and how to develop QR codes for the paper map and concerning applications.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.56 no.3
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• pp.265-276
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• 2020

The objective of this study is to develop education programs for cultivating smart aquaculture experts through a education demand survey of industries, high school students, university (graduate) students and field workers. The industry demand analysis was conducted as an in-depth interview on representives from seven companies. Education demand surveys were conducted on 96 students and field workers in the Jeonnam region. Results on the demand survey were analyzed using frequency analysis and cross-analysis. The company representatives responded that they want to participated in internship and retraining programs to proactively secure manpowers with convergence capabilities about smart aquaculture. Seven companies preferred manpowers with basic competencies on ICT (Information and Communications Technologies) or aquaculture. The most respondents in the demand survey want to participate in the education program for experience on advanced technology, self-development and enhancement of work capability. On the other hand, some respondents said that the education is time-consuming and that the education program does not fit their level. Thus, the education program should be developed in a way to minimize the spatial and temporal limitations of education targets and to improve understanding of non-majors by reflecting the demands of human resources in the industrial field.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.11a
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• pp.101-105
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• 2002

In a traditional hierarchical inventory system, direct orders are the only information for inventory management that is exchanged between the firms involved. But due to the rapid development of modern information technology, it becomes possible for the firms to share more information in real time, e.g. demand and inventory status data. And so the term Supply Chain has emerged because it is seen as an important source of competitive advantage. Now it is possible to challenge traditional approaches to inventory management. In the past, one of the de-facto assumptions for inventory management was that the demand pattern follows a specific distribution function. However, it is undesirable to apply this assumption in real situations because the demand information in the supply chain tends to be distorted due to the bullwhip effect in a supply chain. To overcome this weakness, we propose a new solution method using NN (Neural Network). Our method proceeds in three steps. First, we find the patterns of optimal reorder points by analyzing past data. Second. train the NN using these pattern data and finally decide the reorder point. Using simulation experiment, we show that the proposed solution method gives better result than that of traditional research.