• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2573-2589
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• 2023

As 5G mobile systems carry multiple services and applications, numerous user, and application types with varying quality of service requirements inside a single physical network infrastructure are the primary problem in constructing 5G networks. Radio Access Network (RAN) slicing is introduced as a way to solve these challenges. This research focuses on optimizing RAN slices within a singular physical cell for vehicle-to-everything (V2X) and enhanced mobile broadband (eMBB) UEs, highlighting the importance of adept resource management and allocation for the evolving landscape of 5G services. We put forth two unique strategies: one being offline network slicing, also referred to as standard network slicing, and the other being Online reinforcement learning (RL) network slicing. Both strategies aim to maximize network efficiency by gathering network model characteristics and augmenting radio resources for eMBB and V2X UEs. When compared to traditional network slicing, RL network slicing shows greater performance in the allocation and utilization of UE resources. These steps are taken to adapt to fluctuating traffic loads using RL strategies, with the ultimate objective of bolstering the efficiency of generic 5G services.

• 정보보호학회지
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• 제30권6호
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• pp.17-22
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• 2020

5G 단독모드(StandAlone)가 미국, 중국 등에 상용화됨에 따라 고속 서비스 eMBB(enhanced Mobile BroadBand), 저지연 서비스 URLLC(Ultra Reliable Low Latency Communication), 다 연결 서비스 mMTC(massive Machine-Type Communications) 기술 또한 곧 상용 기술화 될 것으로 예상된다. 이러한 5G 서비스의 기술 개발에는 다양한 기업과 기관들이 참여하여 매년 신규 표준이 생성되고 있다. 따라서 본 논문에서는 5G 보안 표준화에 대한 현황을 파악하여 전반적인 5G 보안 동향에 대한 정보를 제공하고자 한다.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• 전자통신동향분석
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• 제35권6호
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• pp.129-136
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• 2020

Korea launched the world's first commercial 5G services in April 2019. Mobile traffic is expected to increase further with the acceleration of mobile-centric data utilization. It is one of the most important indexes of the growth of the mobile communications market, and it has a close relationship with frequency demand and supply, network management, and information communication policy. To overcome the limitations of an analytical solution due to the high complexity of the real world, this paper estimates the diffusion of 5G users using systemic thinking and the behavior of individual agents. Based on these demand forecasts, contributions to the establishment of strategic policies are suggested. For better understanding, global 5G predictions of subscribers and mobile traffic are also compared.

• 전자통신동향분석
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• 제36권4호
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• pp.13-22
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• 2021

Among the activities of 3GPP for operating 5G-based unmanned aerial vehicles, we introduce several use cases of UAVs in 5G mobile communication such as radio access node onboard UAV, simultaneous support data transmission for UAVs and eMBB users, autonomous UAVs controlled by AI, isolated deployment of radio access through UAV, and separation of UAV service area. From this, we further summarize 5G mobile communication requirements for UAVs, including definition and operational criteria of UAS, UAS remote identification requirements, UAS usage requirements, and performance requirements. Finally, regarding 5G mobile communication-based UAS connectivity, identification and tracking support, we discuss the 3GPP UAV architecture, seven major problems, the proposed solutions to each problem, and propose the results for future specification work.

• 스마트미디어저널
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• 제13권4호
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• pp.33-48
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• 2024

향상된 모바일 광대역(eMBB), 초저지연 및 고신뢰 통신(URLLC), 대규모 기계형 통신(mMTC) 등의 특징을 가진 5G의 등장으로 인해 효율적인 네트워크 관리와 서비스 제공을 위해 증가하는 네트워크 트래픽과 복잡성 해결이 시급한 상황이다.본 논문에서는 기계학습(Machine Learning, ML) 및 딥러닝(Deep Learning, DL)기술을 활용하여 5G 네트워크의 초고속, 초저지연, 초연결성이라는 주요 과제를 해결하면서 네트워크 슬라이싱 및 자원 할당을 동적으로 최적화하는 새로운 접근 방식을 제시한다. 제안된 기법에서는 네트워크 트래픽 및 자원 할당에 대한 예측 모델, 네트워크 대역폭 및 지연 시간을 최적화하면서 동시에 개인 정보와 보안을 향상시키기 위한 연합 학습(FL) 기법을 사용한다. 특히, 본 논문에서는 랜덤 포레스트와 LSTM 등 다양한 알고리듬과 모델의 구현 방법에 대해 자세히 다루며, 이를 통해 5G 네트워크 운영의 자동화와 지능화를 위한 방법론을 제시한다. 마지막으로 제안된 기법을 통해 5G 네트워크에 ML 및 DL을 적용하여 얻을 수 있는 성능향상 효과를 성능평가 및 분석을 통해 검증하고 다양한 산업 응용 분야에서 네트워크 슬라이싱 및 자원 관리 최적화를 위한 솔루션을 제시한다.

• 품질경영학회지
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• 제45권1호
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• pp.1-10
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• 2017

Purpose: Most enterprises adopt six sigma acts to maximize the business performance with raising the executiveness for the project improvements in each parts. But there are little studies about six sigma actual operations in manufacturing whether the six sigma improvements that have injected a lot of budget, efforts, labours and time are run properly. Methods: This study select 31 interviewees who have MBB or BB from 5 large enterprises running six sigma over 10 years and 5 SMEs running six sigma over 5 years to understand and review the operational status of six sigma actions in manufacturing industry and to secure representativeness. This study identify the operational status of six sigma actions and key factors enhancing or impeding execution of six sigma projects through face-to-face interviews and online surveys by e-mail. Results: This study figured out the operational status of six sigma actions and key factors enhancing or impeding execution of six sigma projects. We used SPSS 16.0 for the reliability and the validity of survey data. Conclusion: There can be a lot of different factors that affect six sigma project improvements besides the key factors from this study. More study need to think of the organization characteristics and the basic conditions and to remedy the unreasonable points and defects rather than following foreign companies and enterprises.