• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.125-131
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• 2006

This Paper proposes a new directory-based cache coherence scheme which significantly reduces coherence traffic by omitting unnecessary write-backs to home nodes for migratory exclusively-modified data. The proposed protocol is well matched to such migratory data which are accessed in turn by processors, since write-backs to home nodes are never used for such migratory sharing. The simulation result shows that our protocol dramatically alleviate the coherence traffic, and the traffic reduction could also lead to shorten network latency and execution time.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.480-488
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• 2009

A channel-shared modified accelerative pre-allocation wavelength division multiple access (CMAP-WDMA) media access control (MAC) has been proposed for metro-WDMA networks, as an extension of modified pre-allocation wavelength division multiple access (MAP-WDMA) MAC protocol. Similarly, CAP WDMA as an extension of accelerative pre-allocation wavelength division multiple access (AP-WDMA) MAC protocol. Performance of CMAP- and CAP-WDMA was extensively investigated under several channel sharing methods (CSMs), asymmetric traffic load patterns (TLPs), and non-uniform traffic distribution patterns (TDPs). The result showed that the channel utilization of the CMAP-WDMA always outperforms that of CAP-WDMA at the expense of longer channel access delay for channel shared case while CMAP-WDMA provided higher channel utilization at specific network conditions but always shorter channel access delay than CAP-WDMA for non-channel shared case. Additionally both for CMAP- and CAP-WDMA, determining an effective CSM is a critical design issue because TDPs and TLPs can be neither managed nor expected while CSM is manageable, and the CSM supporting the best channel utilization can be recommended.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1857-1862
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• 2012

It is very difficult to construct and manager public transit, like subway, in small city. In this paper, we suggest full electric vehicle sharing service framework as a public transit system in small city. The suggested system will reduce environment pollution and increase resource usage efficiency. The simulation result shows that the suggested electric vehicle sharing system can reduce traffic congestion and lower city road stress.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.235-237
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• 2003

멀티미디어 데이터 전송이 가능한 초고속 통신망의 발달로 음성을 위주로 서비스하던 과거와는 다른 self-similar 특성을 갖는 데이터 트래픽이 발생된다는 것이 알려지고 있다. 이러한 트래픽은 전통적인 네트워크 해석 방법인 포와송 트래픽 모델과는 상당히 차이가 난다는 것이 여러 트래픽의 측정 결과 나타나고 있다. 본 논문에서는 공유 메모리를 갖는 CS(Complete Sharing), DT(Dynamic Threshold), PO(Push-Out) 그리고, SMXQ(Sharing with Maximum Queue)와 같은 다양한 ATM(Asynchronous Transfer Mode) 스위치의 버퍼 관리 기법을 이용하여 입력포트에 self-similar 성질을 갖는 트래픽이 들어올 때 출력포트에서의 self-similarity와 셀 손실률 그리고, 이용률 등을 분석한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.2
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• pp.381-389
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• 1994

In the communication network, multimedia service such as high quality voice, high speed data, image etc. will be added to the existing service. This service generates new requirements for the communication networks. The priority control mechanism can be used to control multimedia traffics generated by many communication systems. The priority mechanism which assigns prioirities to generated cells according to service quality is one of the traffic control. The priority assignment can be divided by priority criterion for each traffic characteristics such as loss sensitivity and delay sensitivity. In this paper, we alnalyzed the partial buffur sharing (PBS) mechani느 as a traffic control reducing the cell loss, and proposed analysis method. We analyzed the PBS mechanism using classical approach as a Markov chain. In order to validata proposed analysis method, simulation is performed using simulation package SIMSCRIPT 11.5. From this results, we confirmed that proposed analysis method can be verified. Also, we presented cell loss probability of ATM network when this results are to be applied to ATM networks.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.48-57
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• 2020

Recently, with the rapid development of image recognition technology, the demand for object analysis in road CCTV videos is increasing. In this paper, we propose a method that can adaptively find the counting line for traffic analysis in road CCTV videos. First, vehicles on the road are detected, and the corresponding positions of the detected vehicles are modeled as the two-dimensional pointwise Gaussian map. The paths of vehicles are estimated by accumulating pointwise Gaussian maps on successive video frames. Then, we apply clustering and linear regression to the accumulated Gaussian map to find the principal direction of the road, which is highly relevant to the counting line. Experimental results show that the proposed method for detecting the counting line is effective in various situations.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.169-178
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• 2021

Recently, a bike-sharing system (BSS) has become popular as a convenient "last mile" transportation. Rebalancing of bikes is a critical issue to manage BSS because the rents and returns of bikes are not balanced by stations and periods. For efficient and effective rebalancing, accurate traffic prediction is important. Recently, cluster-based traffic prediction has been utilized to enhance the accuracy of prediction at the station-level and the clustering step is very important in this approach. In this paper, we propose a k-means based clustering algorithm that overcomes the drawbacks of the existing clustering methods for BSS; indeterministic and hardly converged. By employing the centroid initialization and using the temporal proportion of the rents and returns of stations as an input for clustering, the proposed algorithm can be deterministic and fast.

• ETRI Journal
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• v.40 no.3
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• pp.355-365
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• 2018

The increase in data traffic calls for investment in mobile networks; however, the saturating revenue of mobile broadband and increasing capital expenditure are discouraging mobile operators from investing in next-generation mobile networks. Mobile network sharing is a viable solution for operators and regulators to resolve this dilemma. This research uses a difference-in-differences analysis of 33 operators (including 11 control operators) to empirically evaluate the cost reduction effect of mobile network sharing. The results indicate a reduction in overall operating expenditure and short-term capital expenditure by national roaming. This finding implies that future technology and standards development should focus on flexible network operation and maintenance, energy efficiency, and maximizing economies of scale in radio access networks. Furthermore, mobile network sharing will become more viable and relevant in a 5G network deployment as spectrum bands are likely to increase the total cost of ownership of mobile networks and technical enablers will facilitate network sharing.

• ETRI Journal
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• v.44 no.2
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• pp.220-231
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• 2022

Building smart transportation services in urban cities has become a worldwide problem owing to the rapidly increasing global population and the development of Internet-of-Things applications. Traffic congestion and environmental concerns can be alleviated by sharing mobility, which reduces the number of vehicles on the road network. The taxi-parcel sharing problem has been considered as an efficient planning model for people and goods flows. In this paper, we enhance the functionality of a current people-parcel taxi sharing model. The adapted model analyzes the historical request data and predicts the current service demands. We then propose two novel online routing algorithms that construct optimal routes in real-time. The objectives are to maximize (as far as possible) both the parcel delivery requests and ride requests while minimizing the idle time and travel distance of the taxis. The proposed online routing algorithms are evaluated on instances adapted from real Cabspotting datasets. After implementing our routing algorithms, the total idle travel distance per day was 9.64% to 12.76% lower than that of the existing taxi-parcel sharing method. Our online routing algorithms can be incorporated into an efficient smart shared taxi system.