• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.109-112
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• 2005

In this thesis, we recommend the method for VOD service traffic modeling. By the analysis of service traffic, we verify that the process of VOD service is the POISSON process. So it is important to determine the probability of the user's existence in the system. But, because it is difficult to measure, we recommend proper using of arrival rate and service rate.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2080-2091
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• 1997

It is generally recognized that Video On Demand (VOD) service will become a promising interactive service in the emerging broadband integrated services digital networks. A centralized VOD system, all programs are stored in a single VOD server which is linked to each user via exchanges, is applicable when a small number of users enjoys the VOD service. However, in case of large service penetration, it is very important to solve the problems of bandwidth and load concentrating in the central video server(CVS) and program transmission network. In this paper, the architecture of the video distribution service network is studied, then a traffic characteristics and models for VOD system are established, and proposed program allocation method to video servers. For this purpose, we present an analysis of program storage amount in each LVS(Local Video Server), transmission traffic volume between LVSs, and link traffic volume between CVS and LVSs, according to changing the related factors such as demand, the number of LVS, vision probability, etc. A method for finding out storage capacity in LVSs is also presented on the basis of the tradeoffs among program storage cost, link traffic cost, and transmission cost.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.1
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• pp.7-17
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• 2010

ITS(Intelligent Transport System) as things are used for Broadcast service using TDMB/TPEG/NAVI rather than personal seamless service. It is attaching weight to Traffic information gathering, Charging, Settlement service. This research is applied to improve DCCP(Datagram Congestion Control Protocol) which has function as protecting data and preserving message boundary. The improving method is like that we solve data trust in UDP because Connection and Transmission overhead in UDP is less than in TCP. We fix the data loss which is generated from unordered delivery section of IP base wireless service by using DCCP protocol. We guarantee of connection with OBE(On-Board Equipment) and reliance about transmission of data by complement to mapping table and multi-hoping. Finally, We evaluate the performance about transmission of IP based data. We constructed a test-bed near research center for this test.

• The Journal of Information Technology
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• v.5 no.4
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• pp.173-183
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• 2002

In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group.

• Electronics and Telecommunications Trends
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• v.34 no.3
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• pp.106-113
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• 2019

Mobile traffic is one of the most important indexes of the growth of the mobile communications market, and it has a close relationship with subscribers' service usage patterns, frequency demand and supply, network management, and information communication policy. The purpose of this paper is to understand mobile data usage in Korea and to suggest the optimal steps for establishing the frequency supply and demand system by researching the traffic trends that reflect the characteristics of radio resources in the mobile communications field. To achieve this goal, attempts were made to increase the possibility of policy use by analyzing and forecasting mobile traffic trends, and to improve the accuracy of the research through the verification of the existing prediction results. The paper ends with a discussion of the necessity of a frequency management system based on data science.

• IE interfaces
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• v.18 no.3
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• pp.333-342
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• 2005

In this paper, we propose an efficient forecasting methodology of the mid and long-term frequency demand in Korea. The methodology consists of the following three steps: classification of basic service group, calculation of effective traffic, and frequency forecasting. Based on the previous studies, we classify the services into wide area mobile, short range radio, fixed wireless access and digital video broadcasting in the step of the classification of basic service group. For the calculation of effective traffic, we use the measures of erlang and bps. The step of the calculation of effective traffic classifies the user and basic application, and evaluates the effective traffic. Finally, in the step of frequency forecasting, different methodology will be proposed for each service group and its applications are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2783-2804
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• 2021

In the network function virtualization environment, dynamic changes in network traffic will lead to the dynamic changes of service function chain resource demand, which entails timely dynamic adjustment of service function chain resource configuration. At present, most researches solve this problem through virtual network function migration and link rerouting, and there exist some problems such as long service interruption time, excessive network operation cost and high penalty. This paper proposes a dynamic adjustment method of service function chain resource configuration for the dynamic changes of network traffic. First, a dynamic adjustment request of service function chain is generated according to the prediction of network traffic. Second, a dynamic adjustment strategy of service function chain resource configuration is determined according to substrate network resources. Finally, the resource configuration of a service function chain is pre-adjusted according to the dynamic adjustment strategy. Virtual network functions combination and virtual machine reusing are fully considered in this process. The experimental results show that this method can reduce the influence of service function chain resource configuration dynamic adjustment on quality of service, reduce network operation cost and improve the revenue of service providers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8B
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• pp.730-738
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• 2004

In this paper, System performance parameters such as throughput, blocking probability and delay have been analyzed and expressed as a function of demanding traffic and service termination, probability, and we centers our discussion at particular downlink port of satellite switch which is capable of switching the individual spot beam and processing the information signals in the packet satellite communications with demand assigned multiple access technique. Delay versus throughput as a function of traffic parameters with several service termination probability can be derived via mathematical formulation and the relative differences of transmission delay is also compared.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.339-353
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• 2012

Mobile communication technology is advancing forward to deliver more connected devices and richer content and applications. The number of subscriptions continues to grow along with an explosive increase in the mobile data traffic demand. Thereby, it creates a significant network capacity shortage concerns for mobile network operators. In order to address this problem, it is essential to increase the network capacity at a low additional cost. The device-to-device (D2D) communication based proximity service is believed to have a promising future mobile communication technology that is capable to create new mobile service opportunities and offload traffic to the eNB. In addition, it is also required to develop new mobile communication services and its business models not only to accommodate the increasing mobile traffic demand but also to foster profitability of mobile business service providers such as the network providers, contents providers and platform providers. In this article, we first analyze current mobile business eco-system in the context of CPNT based value chain. Then, propose service development framework and business model creation methodologies for the device-to-device communication based services in the beyond LTE/LTE-Advanced systems.