• 제목/요약/키워드: 5G mobile network

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A Comparative Study on 3D Data Performance in Mobile Web Browsers in 4G and 5G Environments

  • Nam, Duckkyoun;Lee, Daehyeon;Lee, Seunghyun;Kwon, Soonchul
    • International Journal of Internet, Broadcasting and Communication
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    • 제11권3호
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    • pp.8-19
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    • 2019
  • Since their emergence in 2007, smart phones have advanced up to the point that 5G mobile communication in 2019 started to be commercialized. Accordingly, now it is possible to share 3D modeling files and collaborate by means of a mobile web. As the recently commercialized 5G mobile communication network is so useful in sharing 3D modeling files and collaborating that even large-size geometry files can be transmitted at ultra high speed with ultra low transfer delay. We examines characteristics of major 3D file formats such as STL, OBJ, FBX, and glTF and compares the existing 4G LTE (Long Term Evolution) network with the 5G NR (New Radio) mobile communication network. The loading time and packets of each format were measured depending on the mobile web browser environments. We shows that in comparison with 4G LTE, the loading time of STL and OBJ file formats were reduced as much as 6.55 sec and 9.41 sec, respectively in the 5G NR and Chrome browsers. The glTF file format showed the most efficient performance in all of the 4G/5G mobile communication networks, Chrome, and Edge browsers. In the case of STL and OBJ, the traffic was relatively excessive in 5G NR and Edge browsers. The findings of this study are expected to be utilized to develop a 3D file format that reduces the loading time in a mobile web environment.

5G 모바일 에지 컴퓨팅에서 빅데이터 분석 기능에 대한 데이터 오염 공격 탐지 성능 향상을 위한 연구 (A Study on Improving Data Poisoning Attack Detection against Network Data Analytics Function in 5G Mobile Edge Computing)

  • 옥지원;노현;임연섭;김성민
    • 정보보호학회논문지
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    • 제33권3호
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    • pp.549-559
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    • 2023
  • 5G 네트워크의 핵심 기술로 모바일 에지 컴퓨팅(Mobile Edge Computing, MEC)이 주목받음에 따라, 모바일 사용자의 데이터를 기반으로 한 5G 네트워크 기반 에지 AI 기술이 최근 다양한 분야에서 이용되고 있다. 하지만, 전통적인 인공지능 보안에서와 마찬가지로, 에지 AI 핵심 기능을 담당하는 코어망 내 표준 5G 네트워크 기능들에 대한 적대적 교란이 발생할 가능성이 존재한다. 더불어, 3GPP에서 정의한 5G 표준 내 Standalone 모드의MEC 환경에서 발생할 수 있는 데이터 오염 공격은 기존 LTE망 대비 현재 연구가 미비한 실정이다. 본연구에서는 5G에서 에지 AI의 핵심 기능을 담당하는 네트워크 기능인 NWDAF를 활용하는 MEC 환경에 대한 위협 모델을 탐구하고, 일부 개념 증명으로써 Leaf NWDAF에 대한 데이터 오염 공격 탐지 성능을 향상시키기 위한 특징 선택 방법을 제안한다. 제안한 방법론을 통해, NWDAF에서의 Slowloris 공격 기반 데이터 오염 공격에 대해 최대 94.9%의 탐지율을 달성하였다.

Resource Management in 5G Mobile Networks: Survey and Challenges

  • Chien, Wei-Che;Huang, Shih-Yun;Lai, Chin-Feng;Chao, Han-Chieh
    • Journal of Information Processing Systems
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    • 제16권4호
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    • pp.896-914
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    • 2020
  • With the rapid growth of network traffic, a large number of connected devices, and higher application services, the traditional network is facing several challenges. In addition to improving the current network architecture and hardware specifications, effective resource management means the development trend of 5G. Although many existing potential technologies have been proposed to solve the some of 5G challenges, such as multiple-input multiple-output (MIMO), software-defined networking (SDN), network functions virtualization (NFV), edge computing, millimeter-wave, etc., research studies in 5G continue to enrich its function and move toward B5G mobile networks. In this paper, focusing on the resource allocation issues of 5G core networks and radio access networks, we address the latest technological developments and discuss the current challenges for resource management in 5G.

5G 이동망과 ATSC 3.0 방송망 연동 동향 및 방안 (5G mobile network and ATSC 3.0 broadcasting network interworking trend and plan)

  • 김현철
    • 융합보안논문지
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    • 제20권3호
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    • pp.47-52
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    • 2020
  • 방송 분야에서의 가상화 기술도입은 방송산업 생태계 전반에 걸쳐 IT 자원의 효과적인 운영을 기반으로 방송 서비스 자동화 및 지능화가 활발하게 진행되고 있다. 최근에는 방송망 인프라의 네트워크 가상화를 통해 다양한 방송 자원의 유연성을 높이고 다른 망과의 연동 효율성을 높이고자 하는 관심이 높아지고 있다. 방송망에서 IP 패러다임으로의 근본적인 변환은 인터넷 기반 서비스 플랫폼들과 5G 망과의 효과적인 연동과 신규 융합 서비스 개발을 위한 여러 가지 문제를 해결해야 하는 상황에 직면하고 있다. 즉, 이처럼 ATSC 3.0으로 대표되는 차세대 방송망과 5G 대표되는 이동통신망, 인터넷과의 유기적, 효과적인 연동을 위해서는 수많은 난제를 해결해야 하는 상황이다. 본 논문에서는 ATSC 3.0 방송망과 5G로 대표되는 이동통신망과의 융합을 위한 기본 기술 및 현황을 살펴보고, ATSC 3.0 방송망과 5G 망이 서로 망대 망으로 연동하려는 방안에 관해서 기술하였다.

Mobile Small Cells for Further Enhanced 5G Heterogeneous Networks

  • Lee, Choong-Hee;Lee, Sung-Hyung;Go, Kwang-Chun;Oh, Sung-Min;Shin, Jae Sheung;Kim, Jae-Hyun
    • ETRI Journal
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    • 제37권5호
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    • pp.856-866
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    • 2015
  • A heterogeneous network (HetNet) is a network topology composed by deploying multiple HetNets under the coverage of macro cells (MCs). It can improve network throughput, extend cell coverage, and offload network traffic; for example, the network traffic of a 5G mobile communications network. A HetNet involves a mix of radio technologies and various cell types working together seamlessly. In a HetNet, coordination between MCs and small cells (SCs) has a positive impact on the performance of the networks contained within, and consequently on the overall user experience. Therefore, to improve user-perceived service quality, HetNets require high-efficiency network protocols and enhanced radio technologies. In this paper, we introduce a 5G HetNet comprised of MCs and both fixed and mobile SCs (mSCs). The featured mSCs can be mounted on a car, bus, or train and have different characteristics to fixed SCs (fSCs). In this paper, we address the technical challenges related to mSCs. In addition, we analyze the network performance under two HetNet scenarios-MCs and fSCs, and MCs and mSCs.

Small Cell Communication Analysis based on Machine Learning in 5G Mobile Communication

  • Kim, Yoon-Hwan
    • 통합자연과학논문집
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    • 제14권2호
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    • pp.50-56
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    • 2021
  • Due to the recent increase in the mobile streaming market, mobile traffic is increasing exponentially. IMT-2020, named as the next generation mobile communication standard by ITU, is called the 5th generation mobile communication (5G), and is a technology that satisfies the data traffic capacity, low latency, high energy efficiency, and economic efficiency compared to the existing LTE (Long Term Evolution) system. 5G implements this technology by utilizing a high frequency band, but there is a problem of path loss due to the use of a high frequency band, which is greatly affected by system performance. In this paper, small cell technology was presented as a solution to the high frequency utilization of 5G mobile communication system, and furthermore, the system performance was improved by applying machine learning technology to macro communication and small cell communication method decision. It was found that the system performance was improved due to the technical application and the application of machine learning techniques.

Real-time RL-based 5G Network Slicing Design and Traffic Model Distribution: Implementation for V2X and eMBB Services

  • WeiJian Zhou;Azharul Islam;KyungHi Chang
    • 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.

5G 모바일 네트워크의 Industrial IoT 표준기술 동향 (Industrial IoT Standardization Trend of the 5G Mobile Network)

  • 김경수;강유화;김창기
    • 전자통신동향분석
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    • 제36권6호
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    • pp.13-24
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    • 2021
  • Industrial networks has been developing various technologies from fieldbus technology to industrial Ethernet and time-sensitive networking. The industry expects that the 5G mobile network will solve the diverse and highly specific industrial site requirements. Accordingly, 3GPP has been developing standard functions to provide ultra-high reliability, ultra-high speed, ultra-connection, and ultra-low latency services, and 3GPP Rel-16 began developing ultra-low latency and ultra-high reliability communication functions for 5G mobile networks to support vertical industries. In this paper, we show the related standardization trends and requirements to apply industrial IoT service scenarios to 5G mobile networks, and in particular, we introduce 5G system features and extended 5G system architecture to provide time sensitive communication and time synchronization services.

모바일 네트워크 에너지 절감 기술 동향 (Trends in Mobile Network Energy-Saving Technology)

  • 정수정;홍승은;나지현
    • 전자통신동향분석
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    • 제38권2호
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    • pp.26-35
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    • 2023
  • Energy efficiency is an important factor toward sustainable future mobile network systems. As the size of the 5G mobile network system increases, the consumption and costs of energy increase. Accordingly, energy-saving optimization has become a major process in network systems, and various related technologies for energy saving are being developed. We provide a brief review of the technical trends in energy saving in 3GPP 5G & 5G Advanced systems and O-RAN systems. We focus on power models and energy-saving technologies in various resource domains of 3GPP 5G & 5G Advanced systems and energy-saving use cases of O-RAN systems.

Ultra-low-latency services in 5G systems: A perspective from 3GPP standards

  • Jun, Sunmi;Kang, Yoohwa;Kim, Jaeho;Kim, Changki
    • ETRI Journal
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    • 제42권5호
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    • pp.721-733
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    • 2020
  • Recently, there is an increasing demand for ultra-low-latency (ULL) services such as factory automation, autonomous driving, and telesurgery that must meet an end-to-end latency of less than 10 ms. Fifth-generation (5G) New Radio guarantees 0.5 ms one-way latency, so the feasibility of ULL services is higher than in previous mobile communications. However, this feasibility ensures performance at the radio access network level and requires an innovative 5G network architecture for end-to-end ULL across the entire 5G system. Hence, we survey in detailed two the 3rd Generation Partnership Party (3GPP) standardization activities to ensure low latency at network level. 3GPP standardizes mobile edge computing (MEC), a low-latency solution at the edge network, in Release 15/16 and is standardizing time-sensitive communication in Release 16/17 for interworking 5G systems and IEEE 802.1 time-sensitive networking (TSN), a next-generation industry technology for ensuring low/deterministic latency. We developed a 5G system based on 3GPP Release 15 to support MEC with a potential sub-10 ms end-to-end latency in the edge network. In the near future, to provide ULL services in the external network of a 5G system, we suggest a 5G-IEEE TSN interworking system based on 3GPP Release 16/17 that meets an end-to-end latency of 2 ms.