• Title/Summary/Keyword: Next generation networks

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Low Earth Orbit Satellite Communications, Applications and Major Operators' Service Deployments (저궤도 위성통신의 활용과 주요 사업자의 서비스 전개 현황)

  • G.E. Choi;Y.K. Song
    • Electronics and Telecommunications Trends
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    • v.39 no.3
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    • pp.36-47
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    • 2024
  • Low Earth Orbit (LEO) satellite communications has become a crucial technology for next-generation communication networks owing to its hyperconnectivity capabilities. We examine the progress and application areas of LEO satellite communication services. The LEO satellite communication industry has transitioned from being predominantly driven by governments and institutions to being led by the private sector, following the trajectory of the NewSpace movement. Leading corporations such as SpaceX Starlink and Eutelsat OneWeb are deploying LEO satellite networks to offer internet services, while Telesat is preparing to establish its satellite communication network. LEO satellite communications is expected to have a major impact on various sectors of society, particularly for upcoming sixth-generation services. Therefore, the South Korean government must promptly formulate policy support strategies aimed at invigorating the LEO satellite communication industry. This can be achieved through initiatives such as bolstering research and development and extending corporate assistance.

Virtual Source and Flooding-Based QoS Unicast and Multicast Routing in the Next Generation Optical Internet based on IP/DWDM Technology (IP/DWDM 기반 차세대 광 인터넷 망에서 가상 소스와 플러딩에 기초한 QoS 제공 유니캐스트 및 멀티캐스트 라우팅 방법 연구)

  • Kim, Sung-Un;Park, Seon-Yeong
    • Journal of Korea Multimedia Society
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    • v.14 no.1
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    • pp.33-43
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    • 2011
  • Routing technologies considering QoS-based hypermedia services have been seen as a crucial network property in next generation optical Internet (NGOI) networks based on IP/dense-wavelength division multiplexing (DWDM). The huge potential capacity of one single fiber. which is in Tb/s range, can be exploited by applying DWDM technology which transfers multiple data streams (classified and aggregated IP traffics) on multiple wavelengths (classified with QoS-based) simultaneously. So, DWDM-based optical networks have been a favorable approach for the next generation optical backbone networks. Finding a qualified path meeting the multiple constraints is a multi-constraint optimization problem, which has been proven to be NP-complete and cannot be solved by a simple algorithm. The majority of previous works in DWDM networks has viewed heuristic QoS routing algorithms (as an extension of the current Internet routing paradigm) which are very complex and cause the operational and implementation overheads. This aspect will be more pronounced when the network is unstable or when the size of network is large. In this paper, we propose a flooding-based unicast and multicast QoS routing methodologies(YS-QUR and YS-QMR) which incur much lower message overhead yet yields a good connection establishment success rate. The simulation results demonstrate that the YS-QUR and YS-QMR algorithms are superior to the previous routing algorithms.

Subword Neural Language Generation with Unlikelihood Training

  • Iqbal, Salahuddin Muhammad;Kang, Dae-Ki
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.2
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    • pp.45-50
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    • 2020
  • A Language model with neural networks commonly trained with likelihood loss. Such that the model can learn the sequence of human text. State-of-the-art results achieved in various language generation tasks, e.g., text summarization, dialogue response generation, and text generation, by utilizing the language model's next token output probabilities. Monotonous and boring outputs are a well-known problem of this model, yet only a few solutions proposed to address this problem. Several decoding techniques proposed to suppress repetitive tokens. Unlikelihood training approached this problem by penalizing candidate tokens probabilities if the tokens already seen in previous steps. While the method successfully showed a less repetitive generated token, the method has a large memory consumption because of the training need a big vocabulary size. We effectively reduced memory footprint by encoding words as sequences of subword units. Finally, we report competitive results with token level unlikelihood training in several automatic evaluations compared to the previous work.

SDN-Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra-Dense Small Cell Networks

  • Yang, Guang;Cao, Yewen;Esmailpour, Amir;Wang, Deqiang
    • ETRI Journal
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    • v.40 no.2
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    • pp.227-236
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    • 2018
  • Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

An analysis of learning performance changes in spiking neural networks(SNN) (Spiking Neural Networks(SNN) 구조에서 뉴런의 개수와 학습량에 따른 학습 성능 변화 분석)

  • Kim, Yongjoo;Kim, Taeho
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.3
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    • pp.463-468
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    • 2020
  • Artificial intelligence researches are being applied and developed in various fields. In this paper, we build a neural network by using the method of implementing artificial intelligence in the form of spiking natural networks (SNN), the next-generation of artificial intelligence research, and analyze how the number of neurons in that neural networks affect the performance of the neural networks. We also analyze how the performance of neural networks changes while increasing the amount of neural network learning. The findings will help optimize SNN-based neural networks used in each field.

A Study of Fronthaul Networks in CRANs - Requirements and Recent Advancements

  • Waqar, Muhammad;Kim, Ajung;Cho, Peter K.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.4618-4639
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    • 2018
  • One of the most innovative paradigms for the next-generation of wireless cellular networks is the cloud-radio access networks (C-RANs). In C-RANs, base station functions are distributed between the remote radio heads (RHHs) and base band unit (BBU) pool, and a communication link is defined between them which is referred as the fronthaul. This leveraging link is expected to reduce the CAPEX (capital expenditure) and OPEX (operating expense) of envisioned cellular architectures as well as improves the spectral and energy efficiencies, provides the high scalability, and efficient mobility management capabilities. The fronthaul link carries the baseband signals between the RRHs and BBU pool using the digital radio over fiber (RoF) based common public radio interface (CPRI). CPRI based optical links imposed stringent synchronization, latency and throughput requirements on the fronthaul. As a result, fronthaul becomes a hinder in commercial deployments of C-RANs and is seen as one of a major bottleneck for backbone networks. The optimization of fronthaul is still a challenging issue and requires further exploration at industrial and academic levels. This paper comprehensively summarized the current challenges and requirements of fronthaul networks, and discusses the recently proposed system architectures, virtualization techniques, key transport technologies and compression schemes to carry the time-sensitive traffic in fronthaul networks.

A Congestion Control Mechanism for Supporting Differentiated Service in Mobile Ad hoc Networks

  • Kim Jin-Nyun;Ha Nam-Koo;Cho Dong-Hoon;Kim Hyun-Sook;Han Ki-Jun
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.143-146
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    • 2004
  • Differentiated services (DiffServ) has been widely accepted as the service model to adopt for providing quality-of­service (QoS) over the next-generation IP networks. There is a growing need to support QoS in mobile ad hoc networks. Supporting DiffServ in mobile ad hoc networks, however, is very difficult because of the dynamic nature of mobile ad hoc networks, which causes network congestion. The network congestion induces long transfer packet delay and low throughput which make it very difficult to support QoS in mobile ad hoc networks. We propose DiffServ module to support differentiated service in mobile ad hoc networks through congestion control. Our DiffServ module uses the periodical rate control for real time traffic and also uses the best effort bandwidth concession when network congestion occurs. Network congestion is detected by measuring the packet transfer delay or bandwidth threshold of real time traffic. We evaluate our mechanism via a simulation study. Simulation results show our mechanism may offer a low and stable delay and a stable throughput for real time traffic in mobile ad hoc networks.

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QoS-Aware Bounded Flooding RWA Algorithm in the Next Generation Optical Internet based on DWDM Networks (DWDM기반의 차세대 광인터넷에서 QoS 기반의 제한적 플러딩 RWA 알고리즘에 관한 연구)

  • Kim Yong-Seong;Lee Jae-Dong;Hwang Jin-Ho;Woo Chong-Ho
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.43 no.8 s.350
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    • pp.1-14
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    • 2006
  • Multi-constraint QoS routing has been seen as crucial network property in the next generation optical Internet based on DWDM Networks. This paper proposes a new QoS routing algorithm based on flooding method, called bounded flooding routing (BFR) algorithm which can meet multi-constraint QoS requirements. Primarily, the BFR algorithm tries to reduce network overhead by accomplishing bounded-flooding to meet QoS requirements, and improve blocking probability and wavelength utilization. Also, as one effort to improve routing performance, we introduce a new concept, ripple count, which does not need any link-state information and computational process. For extensive analysis and simulation study, as a critical concern, in DWDM-based networks we deploy limited wavelength conversion capability within DWDM nodes. And the simulation results demonstrate that the BFR algorithm is superior to other predominant routing algorithms (both original flooding method and source-directed methods) in terms of blocking probability, wavelength channels required and overhead.

Design and Verification of Flow Mobility Scheme tn the AIMS System (AIMS 시스템에서 플로우 이동성 기법의 설계와 검증)

  • Lee, Sung-Kuen;Lee, Kyoung-Hee;Min, Sung-Gi;Lee, Hyo-Beom;Lee, Hyun-Woo;Han, Youn-Hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.7B
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    • pp.760-770
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    • 2011
  • The existing mobility management schemes do not fully support the next generation network, which is composed of IP-based core network and various access networks. Currently, ETRI has been developing the AIMS (Access Independent Mobility Service) system which satisfies the ITU-T requirements of mobility management in the next generation network. The AIMS system is designed to provide a mobile host with a fast and reliable mobility service among heterogeneous access networks. Recently, many user devices have multiple communication interfaces, e.g., 3G and WLAN, and thus they can make two or more network connections at the same time. In this paper, we design a scheme of flow mobility, i.e., the movement of selected data flows from one access technology to another, to be applied in the AIMS system, and verify the proposed scheme through the NS-3 simulation study. From the simulation results, we can know that the proposed flow mobility scheme can utilize the network resource efficiently in the heterogeneous mobile networks.

Development of Photovoltaic Output Power Prediction System using OR-AND Structured Fuzzy Neural Networks (OR-AND 구조의 퍼지 뉴럴 네트워크를 이용한 태양광 발전 출력 예측 시스템 개발)

  • Kim, Haemaro;Han, Chang-Wook;Lee, Don-Kyu
    • Journal of IKEEE
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    • v.23 no.1
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    • pp.334-337
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    • 2019
  • In response to the increasing demand for energy, research and development of next-generation energy is actively carried out around the world to replace fossil fuels. Among them, the specific gravity of solar power generation systems using infinity and pollution-free solar energy is increasing. However, solar power generation is so different from solar energy that it is difficult to provide stable power and the power production itself depends on the solar energy by region. To solve these problems in this paper, we have collected meteorological data such as actual regional solar irradiance, precipitation, temperature and humidity, and proposed a solar power output prediction system using logic-based fuzzy Neural Network.