• ETRI Journal
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• 제27권1호
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• pp.110-113
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• 2005

The resilient packet ring (RPR) is a data optimized ring network, where one of the key issues is on load balancing for competing streams of elastic traffic. This paper suggests three efficient traffic loading algorithms on the RPR. For the algorithms, we evaluate their efficiency via analysis or simulation.

• 스마트미디어저널
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• 제11권5호
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• pp.82-90
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• 2022

Along with the growing popularity of 5G technology, providing flexible and personalized network services suitable for requirements of customers has also become a lucrative venture and business key for network service providers. Therefore, dynamic network provisioning is needed to help network service providers. Moreover, increasing user demand for network services meets specific requirements of users, including location, usage duration, and QoS. In this paper, a routing algorithm, which makes routing decisions using Reinforcement Learning (RL) based on the information about link stability, is proposed and called Link Stability aware Reinforcement Learning (LSRL) routing. To evaluate this algorithm, several mininet-based experiments with various network settings were conducted. As a result, it was observed that the proposed method accepts more requests through the evaluation than the past link annotated shorted path algorithm and it was demonstrated that the proposed approach is an appealing solution for dynamic network provisioning routing.

• 한국통신학회논문지
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• 제41권10호
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• pp.1290-1300
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• 2016

최근 들어, 유무선 망의 종단 사이에 위치하여 다양한 네트워크 기능을 제공하는 미들박스 서비스가 일반화되고 있다. 특히, 클라우드 컴퓨팅 분야의 가상화 기술이 네트워크 분야에 적용되면서 네트워크 가상화가 빠르게 진행되고, 가상 네트워크 장비들을 유연하게 연결하여 민첩한 네트워크 서비스를 제공하는 플랫폼들이 연구되고 있다. 본 논문에서는 캐리어 급 미들박스 서비스를 제공하기 위한 필수 요소들을 살펴보고, 범용서버에서 캐리어 급 네트워크 주소 변환 서비스를 제공하기 위한 프레임워크의 설계와 구현에 대해 기술한다. 실험 결과에 의하면, 제안하는 프레임워크는 기존의 리눅스 커널에서 제공하는 주소 변환 기능보다 15.5배 빠른 성능을 보인다.

• International journal of advanced smart convergence
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• 제6권4호
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• pp.67-72
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• 2017

Deep learning neural network becomes very popular nowadays due to the reason that it can learn a very complex dataset such as the image dataset. Although deep learning neural network can produce high accuracy on the image dataset, it needs a lot of time to reach the convergence stage. To solve the issue, we have proposed a scaling method to improve the neural network to achieve the convergence stage in a shorter time than the original method. From the result, we can observe that our algorithm has higher performance than the other previous work.

• 대한산업공학회지
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• 제42권3호
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• pp.182-197
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• 2016

One of the distinctive characteristics of industrial engineering (IE) is its multidisciplinarity. This paper explores the multidisciplinary nature of IE using journal citation network analysis. Using the relatedness indexes of IE journals obtained from journal citation report (JCR), we firstly construct the IE network only composed of 26 IE journals. The resulting IE network is partitioned into three sub-networks: management engineering, manufacturing/quality, and ergonomics. We then propose the IE convergence network which includes 81 related journals in other disciplines as well as 26 IE journals. Scrutinizing the IE convergence network reveals that IE has a high degree of interactions with seven disciplines : Operations Research and Management Science, Statistics and Probability, Manufacturing Engineering, Computer Science, Engineering Design, Business Management, Human Factors and Ergonomics. We investigate the contributions of the related disciplines to IE as well as contributions of IE to the related disciplines. The role of IE journals in exchanging knowledge with related disciplines is also identified by brokerage analysis. It is shown that visualizing and analyzing the IE convergence network can provide an excellent overview of the multidisciplinary structure of IE, which can help IE researchers easily grasp the state-of-the art of IE research.

• 한국산업융합학회 논문집
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• 제25권4_2호
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• pp.627-636
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• 2022

Market convergence plays an increasingly important role in sustaining competitiveness and providing impetus for the new product development. However, existing research focused mostly on the analysis of convergence at technology level. This study examines the phenomenon of market convergence based on the start-up data. Similar to the analysis of technology convergence, this study adopts the concept of co-classification analysis for constructing the co-occurrence matrix and the corresponding network. In this context, network centrality measures were calculated to assess the influence of individual market segments. Based on three metrics "growth", "persistence" and "novelty", the market convergence dynamics were explored and promising interactions between two distinct market segments were highlighted. The findings suggest that both segments "AI" and "blockchain" are acting as a driver that fosters market convergence in the startup landscape. The analysis results can provide valuable information for the R&D managers and policy makers in the design of targeted policies and programs, which can promote market convergence and interdisciplinary knowledge transfer.

• 지식경영연구
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• 제16권2호
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• pp.113-137
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• 2015

Many scholars have addressed the technological convergence of small-medium sized firms in Korea and their impact on the economic growth of nation. Nevertheless, most studies have been investigated the relationship between entrepreneurship and venture creation, and a few studies have analyzed the innovation and technological convergence of SMEs. The purpose of this research is to gain industrial insight into the technological convergence and to suggest a dynamic growth policy for entrepreneurs of SMEs to improve their convergence performance based on IT and BT. Therefore, we intend to propose solutions to these key questions in convergence such as; what are the key patterns in the process of technological convergence of SMEs on IT and BT, and what kinds of strategy do their need? In order to answer these research questions, we adopt network analysis using patent citation information. Results of network analysis revealed that building ecosystem based on government and universities is one of the most important factors for the future growth of SMEs in Korea. Also, the fit between technological convergence direction of SMEs and division of convergence structure of government and universities will be positively associated with dynamic growth of SMEs in Korea. In conclusion, this research extends the current studies on important aspects of SMEs in the technological convergence process by proposing their growth in convergence process to a newly converging context, IT and BT, and shed light on the integrative perspectives of crucial roles of SMEs on innovation performance in the IT and BT technological convergence.

• 기술혁신학회지
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• 제18권4호
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• pp.693-718
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• 2015

본 연구는 국가과학기술연구회(구, 기초기술연구회 및 산업기술연구회) 산하 출연연 24개 기관이 출연금과 정부수탁과제로 집행한 최근 3개년간(2011~2013)의 연구과제중 국가과학기술표준분류의 중 분류 기준으로 2개 이상의 기술을 연구하는 융합기술 연구과제를 사회연결망분석 기법을 활용하여 기술간에 어떠한 네트워크 구조를 가지고 있는지를 분석해 보았다. 분석결과 출연연의 융합연구는 국가연구개발사업의 전체 융합연구와 비교할 때 더 활발하고, 다양한 기술분야에서 수행되고 있음을 확인할 수 있었다. 또한 외부기관과 공동연구에 의한 융합연구보다 내부에서 더 활발히 융합연구가 이루어지고 있음을 확인하였다. 그리고 융합기술의 네트워크 중심성을 파악하여 융합연구의 중심역할을 하는 기술이 내부중심형 기술과 외부중심형 기술로 분류된다는 것을 확인하였다. 융합연구는 단순히 기술간의 융합만을 뜻하는 것은 아니다. 출연연은 융합연구 활성화를 위해서 단순히 다기술 연구만을 수행하지 말고, 신기술, 신산업을 창출할 수 있는 융합연구 영역도 창출해야 할 것이다. 이러한 관점에서 본 논문은 출연연의 융합연구 현황 및 네트워크 분석을 통해 출연연의 융합연구를 활성화를 위한 역할에 대한 정책적 시사점을 제시하고 있다.

• 경영과학
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• 제23권2호
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• pp.161-174
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• 2006

In this paper, we consider a network optimization problem arising from the deployment of BcN access network. BcN convergence services requires that access networks satisfy QoS meausres. BcN services have two types of traffics : stream traffic and elastic traffic. Stream traffic uses blocking probability as a QoS measure, while elastic traffic uses delay factor as a QoS measure. Incorporating the QoS requirements, we formulate the problem as a nonlinear mixed-integer Programming model. The Proposed model seeks to find a minimum cost dimensioning solution, while satisfying the QoS requirement. We propose two local search heuristic algorithms for solving the problem, and develop a network design system that implements the developed heuristic algorithms. We demonstrate the computational efficacy of the proposed algorithm by solving a realistic network design problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1063-1082
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• 2018

The concept of SDN (Software Defined Networking) endows the network with programmability and significantly improves the flexibility and extensibility of networks. Currently a plenty of research works on introducing SDN into wireless networks. Most of them focus on the innovation of the SDN based architectures but few consider how to realize the global perception of the network through the controller. In order to address this problem, a software defined carrier grade Wi-Fi framework called SWAN, is proposed firstly. Then based on the proposed SWAN architecture, a blueprint of introducing the traditional NSA (Network Situation Awareness) into SWAN is proposed and described in detail. Through perceiving various network data by a decentralized architecture and making comprehension and prediction on the perceived data, the proposed blueprint endows the controllers with the capability to aware of the current network situation and predict the near future situation. Meanwhile, the extensibility of the proposed blueprint makes it a universal solution for software defined wireless networks SDWNs rather than just for one case. Then we further research one typical use case of proposed NSA blueprint: network performance awareness (NPA). The subsequent comparison with other methods and result analysis not only well prove the effectiveness of proposed NPA but further provide a strong proof of the feasibility of proposed NSA blueprint.