• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.549-558
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• 2018

We designed and implemented streaming server based on MEPG DASH, which is able to provide high quality video with low-latency live streaming service like 360 VR video on the existing cable network via low-spec media service devices such as IPTV and OTT(Over the Top) SettopBox. We also designed and applied management process which is cable of supporting services by cashing streaming video file(MPD, Segment Files) to reduce the server response delay time. Further more, we confimred that it is also able to provide high quality of tiled video streaming with over 50,000kbps bitrate and 8K@60P through the experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.350-353
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• 2014

The large scale of data and operating systems in the trading environment in the cloud. However, technology is not an easy trading system of cloud-based data interoperability. Partially meets the data transfer rate and also the timeliness of the best trading system on the difficulties. Thus various techniques have been introduced for improving the throughput and low latency minimization problem. But the reality is, and the limits of speed improvements like Socket Direct Protocol, Offload Engine with TCP/IP is the hardware, the introduction effect is also low. In this paper, the proposed trading of the cloud XMDR-DAI based stock system. The proposed Safe Proper Time Method for optimal transmission speed and reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• 한국정보통신설비학회:학술대회논문집
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• 2006.08a
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• pp.43-46
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• 2006

IEEE 802.16 WirelessMAN aiming to broadband wireless access (BWA) is evolving to 4G mobile communication system through the standardization of IEEE 802.16e supporting mobility on existing fixed WirelessMAN system. It is necessary for hand-over to provide seamless data service while MS (Mobile Station) moves to another BS (Base Station). Because the performance of handover affects packet loss or delay of any communications, it must consider low latency handover mechanism in packet based network. In this paper, we describes handover scheme of IEEE 802.16e with the cell edge interference problem and shows the way to solve the problem in frequency reuse one deployment. Our scheme reduces the handover latency and packet loss probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.473-493
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• 2019

5G vehicular communication is one of key enablers in next generation intelligent transportation system (ITS), that require ultra-reliable and low latency communication (URLLC). To meet this requirement, a new hybrid vehicular network structure which supports both centralized network structure and distributed structure is proposed in this paper. Based on the proposed network structure, a new vehicular network utility model considering the latency and reliability in vehicular networks is developed based on Euclidean norm theory. Building on the Pareto improvement theory in economics, a vehicular network uplink optimization algorithm is proposed to optimize the uplink utility of vehicles on the roads. Simulation results show that the proposed scheme can significantly improve the uplink vehicular network utility in vehicular networks to meet the URLLC requirements.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.34-47
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• 2021

To realize remote surgery from hundreds of kilometers away, a new communication environment with ultra-low latency and high-precision features is required. Thus, ultra-high precision networking technology that guarantees the maximum latency and jitter of end-to-end traffic on an Internet-scale wide area network is in development as part of 6G network research. This paper describes the current status of various networking technologies in ITU-T, ETSI, IEEE, and IETF to ensure ultra-low latency and high precision in wired networks.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.157-163
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• 2023

Recently, as businesses and data types become more complex and diverse, efficient data analysis using machine learning is required. However, since communication in the cloud environment is greatly affected by network latency, data analysis is not smooth if information delay occurs. In this paper, SPT (Safe Proper Time) was applied to the cluster-based machine learning data analysis agent proposed in previous studies to solve this delay problem. SPT is a method of remotely and directly accessing memory to a cluster that processes data between layers, effectively improving data transfer speed and ensuring timeliness and reliability of data transfer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.55-62
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• 2018

VANET is a rapidly emerging service area with strict requirements of a few milliseconds' latency. Because current systems don't guarantee ultra-low latency, it has been proposed a latency-guaranteed Autonomous ATDMA(ATDMA) in which autonomous joining/leaving is allowed without coordinator's scheduling. In this study, we extended ATDMA to operate in non-perfect decoding environments with existing hidden nodes, channel fading and node density variation, and named it ATDMA revision(ATDMA-R). We also evaluated the performance of ATDMA and ATDMA-R, and showed the robustness of ATDMA-R through various realistic simulation scenarios.

• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.855-861
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• 2021

Neural Architecture Search (NAS) is cutting-edge technology in the machine learning community. NAS Without Training (NASWOT) recently has been proposed to tackle the high demand of computational resources in NAS by leveraging some indicators to predict the performance of architectures before training. The advantage of these indicators is that they do not require any training. Thus, NASWOT reduces the searching time and computational cost significantly. However, NASWOT only considers high-performing networks which does not guarantee a fast inference speed on hardware devices. In this paper, we propose a multi objectives reward function, which considers the network's latency and the predicted performance, and incorporate it into the Reinforcement Learning approach to search for the best networks with low latency. Unlike other methods, which use FLOPs to measure the latency that does not reflect the actual latency, we obtain the network's latency from the hardware NAS bench. We conduct extensive experiments on NAS-Bench-201 using CIFAR-10, CIFAR-100, and ImageNet-16-120 datasets, and show that the proposed method is capable of generating the best network under latency constrained without training subnetworks.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.105-113
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• 2022

In this paper, we present and analyze 5G system and IEEE time-sensitive networking(TSN) and propose a novel mobility management scheme for time sensitive communications in 5G-TSN to support ultra-low latency networks. Time-sensitive networking(TSN) has a promising future in the Industrial Automation and Industrial Internet of Things(IIoT), as a key technology that is able to provide low-latency, high-reliable and deterministic communications over the Ethernet. When a TSN capable UE moves the TSN service coverage from the non-TSN service coverage, the UE cannot get the TSN service promptly because the related mobility management is not performed appropriately. For the mobility situation with the TSN service coverage, the proposed scheme reports TSN capability to the network and triggers the initial registration in order to be provided the TSN service immediately and ultra-low latency communications compared to existing schemes in 5G mobile networks.