• 정보관리학회지
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• 제25권2호
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• pp.157-166
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• 2008

본 연구에서는 ASIST 프로시딩을 인용한 저널들을 중심으로 패스파인더 네트워크 분석을 수행함으로써, ASIST 프로시딩의 지식이 어떠한 주제영역을 중심으로 네트워크 구조를 형성하고 있는지를 확인하는 데에 그 목적이 있다. 이를 위하여 Scopus 데이터베이스에서 검색한 240개의 문헌을 대상으로 완전연결 클러스터링 기법을 통하여 16개 클러스터를 도출하였으며, MDS 및 패스파인더 네트워크 분석을 통하여 지식 네트워크를 매핑하였다. 지금까지 대부분의 경우 학술지를 대상으로 수행되어 온 네트워크 분석을 프로시딩을 대상으로 분석을 시도하였으며, 분석결과 ASIST 프로시딩은 정보추구행태 및 탐색과 인터페이스, 계량서지학 및 지식관리 주제영역의 논문이 타 문헌에 활발하게 소비되고 있음을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3399-3419
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• 2020

In the Vehicular Ad-hoc Network (VANET), the data transmission of time-sensitive applications requires low latency, such as accident warnings, driving guidance, etc. However, frequent changes of topology in VANET will result in data transmission failures. In order to improve the efficiency of VANETs data transmission and increase the timeliness of data, this paper proposes a relay scheme based on Recurrent Neural Network (RNN) trajectory prediction, which can be used to select the optimal relay vehicle to transmit data. The proposed scheme learns vehicle trajectory in a distributed manner and calculates the predicted trajectory, and then the optimal vehicle can be selected to complete the data transmission, which ensures the timeliness of the data. Finally, we carry out a set of simulations to demonstrate the performance of the algorithm. Simulation results show that the proposed scheme enhances the timeliness of the data and the accuracy of the predicted driving trajectory.

• International journal of advanced smart convergence
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• 제1권1호
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• pp.19-26
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• 2012

The deployment of mobile femtocellular networks can enhance the service quality for the users inside the vehicles. The deployment of mobile femtocells generates a lot of handover calls. Also, numbers of group handover scenarios are found in mobile femtocellular network deployment. The ability to seamlessly switch between the femtocells and the macrocell networks is a key concern for femtocell network deployment. However, until now there is no effective and complete handover scheme for the mobile femtocell network deployment. Also handover between the backhaul networks is a major concern for the mobile femtocellular network deployment. In this paper, we propose handover control between the access networks for the individual handover cases. Call flows for the handover between the backhaul networks of the macrocell-to-macrocell case are proposed in this paper. We also propose the link switching for the FSO based backhaul networks. The proposed resource allocation scheme ensures the negligible handover call dropping probability as well as higher bandwidth utilization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4197-4219
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• 2017

Cloud computing is a new service to provide dynamic, scalable virtual resource services via the Internet. Cloud market is available to multiple cloud computing resource providers and users communicate with each other and participate in market transactions. However, since cloud computing is facing with more and more security issues, how to complete the allocation process effectively and securely become a problem urgently to be solved. In this paper, we firstly analyze the cloud resource allocation problem and propose a mathematic model based on combinatorial double auction. Secondly, we introduce a trust evaluation mechanism into our model and combine genetic algorithm with simulated annealing algorithm to increase the efficiency and security of cloud service. Finally, by doing the overall simulation, we prove that our model is highly effective in the allocation of cloud resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.4117-4135
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• 2020

Due to the angle of view, illumination and scene diversity, real-time dynamic face detection and recognition is no small difficulty in those unrestricted environments. In this study, we used the intrinsic correlation between detection and calibration, using a multi-task cascaded convolutional neural network(MTCNN) to improve the efficiency of face recognition, and the output of each core network is mapped in parallel to a compact Euclidean space, where distance represents the similarity of facial features, so that the target face can be identified as quickly as possible, without waiting for all network iteration calculations to complete the recognition results. And after the angle of the target face and the illumination change, the correlation between the recognition results can be well obtained. In the actual application scenario, we use a multi-camera real-time monitoring system to perform face matching and recognition using successive frames acquired from different angles. The effectiveness of the method was verified by several real-time monitoring experiments, and good results were obtained.

• 한국정보처리학회논문지
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• 제2권3호
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• pp.417-424
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• 1995

본 논문에서는 정량화(Quantification) 문제를 MFT(Mean Field Theroy)를 통해서 해결하는 기법을 제안한다. 통계학에서 중요한 문제의 하나인 정량화 문제는 주어진 공간에서 대상들간의 유사성에 따라서 최적의 상태를 갖도록 하는 문제이다. 평균장 접근 방법에 기초한 한개의 변수로 표현되는 확률적 시뮬레이티드 아닐링을 제안하고 정량화 문제를 패널티(penalty) 파라메타 항을 첨가한 비한정된 최적화 문제로 변형하 여 MFT를 적용하였다. 또한 연속변수를 갖는 신경회로망에서 실제 값을 계산하는 것 보다 평균장 접근방법으로 계산하는것이 더 빠르게 계산될 수 있음을 확인하였다. 본 논문에서 제안한 방법이 실험결과 해석적인 방법보다 좋은 정량적 결과를 보였다.

• 디지털콘텐츠학회 논문지
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• 제18권5호
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• pp.905-910
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• 2017

본 논문에서는 재난안전통신망의 전체 구조가 아닌 재난현장에서 소방대원과 현장 지휘통제실간의 정보교환이 효과적으로 이루어질 수 있도록 재난현장 지역 내의 독립적 네트워크 인프라(무선통신, 영상전송 및 현장상황파악 등) 확보를 위한 현장형 스마트 통합관제시스템을 제안하였다. 제안한 재난환경 스마트 통합 관제시스템은 재난현장에서 현장대원간의 무선통신을 지원하고, 재난현장 영상정보 수집을 위한 드론과의 통신을 지원함으로써 현장 관제시스템에서 재난상황에 대한 전체 주변 영상확보 및 현장대원의 효율적 지휘가 가능하게 된다.

• 한국정보통신학회논문지
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• 제6권1호
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• pp.30-35
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• 2002

동적 라우팅은 최적경로를 선택하고 라우팅테이블을 업데이트 하기 위해 라우팅 프로토콜을 사용한다. 가장 널리 사용되는 라우팅 프로토콜은 거리벡터 알고리즘을 이용한 라우팅인포메이션 프로토콜(RIP)이다. RIP는 최적경로서 최저 흡수의 경로를 취한다. 하지만 이 RIP는 매우 심각한 단점을 가지고 있다. 그것은 15 흡수 이상의 목적지에 대한 네트워크의 라우팅테이블을 유지할 수 없다는 것이다. 이를 극복하기 위해 TCP/IP에서 개발된 링크상태 프로토콜인 OSPF가 사용된다. OSPF는 큰 네트워크에 적합하고 RIP가 갖은 단점들을 극복 했다. 본 논문은 동일한 네트워크에서 메세지 전달과 지연, 링크 사용율, 메세지 전달갯수 같은 두 프로토콜사이의 트래픽과 링크효율을 분석하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권1호
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• pp.68-82
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• 2011

Wireless mesh networks (WMNs) provide high-speed backbone networks without any wired cable. Many researchers have tried to increase network throughput by using multi-channel and multi-radio interfaces. A multi-radio multi-channel WMN requires channel assignment algorithm to decide the number of channels needed for each link. Since the channel assignment affects routing and interference directly, it is a critical component for enhancing network performance. However, the optimal channel assignment is known as a NP complete problem. For high performance, most of previous works assign channels in a centralized manner but they are limited in being applied for dynamic network environments. In this paper, we propose a simple flow estimation algorithm and a hybrid channel assignment algorithm. Our flow estimation algorithm obtains aggregated flow rate information between routers by packet sampling, thereby achieving high scalability. Our hybrid channel assignment algorithm initially assigns channels in a centralized manner first, and runs in a distributed manner to adjust channel assignment when notable traffic changes are detected. This approach provides high scalability and high performance compared with existing algorithms, and they are confirmed through extensive performance evaluations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3138-3150
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• 2021

Multimedia services on the Internet are continuously increasing. Accordingly, the demand for a technology for efficiently delivering multimedia traffic is also constantly increasing. The multicast technique, that delivers the same content to several destinations, is constantly being developed. This technique delivers a content from a source to all destinations through the multicast tree. The multicast tree with low cost increases the utilization of network resources. However, the finding of the optimal multicast tree that has the minimum link costs is very difficult and its calculation complexity is the same as the complexity of the Steiner tree calculation which is NP-complete. Therefore, we need an effective way to obtain a multicast tree with low cost and less calculation time on SDN-based smart network platforms. In this paper, we propose a new multicast tree generation algorithm which produces a multicast tree using an agent trained by model-based meta reinforcement learning. Experiments verified that the proposed algorithm generated multicast trees in less time compared with existing approximation algorithms. It produced multicast trees with low cost in a dynamic network environment compared with the previous DQN-based algorithm.