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201 results on '"Ko, Haneul"'

2. Edge Network-Assisted Real-Time Object Detection Framework for Autonomous Driving

Author

Kim, Seung Wook, Ko, Keunsoo, Ko, Haneul, and Leung, Victor C. M.

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Autonomous vehicles (AVs) can achieve the desired results within a short duration by offloading tasks even requiring high computational power (e.g., object detection (OD)) to edge clouds. However, although edge clouds are exploited, real-time OD cannot always be guaranteed due to dynamic channel quality. To mitigate this problem, we propose an edge network-assisted real-time OD framework~(EODF). In an EODF, AVs extract the region of interests~(RoIs) of the captured image when the channel quality is not sufficiently good for supporting real-time OD. Then, AVs compress the image data on the basis of the RoIs and transmit the compressed one to the edge cloud. In so doing, real-time OD can be achieved owing to the reduced transmission latency. To verify the feasibility of our framework, we evaluate the probability that the results of OD are not received within the inter-frame duration (i.e., outage probability) and their accuracy. From the evaluation, we demonstrate that the proposed EODF provides the results to AVs in real-time and achieves satisfactory accuracy., Comment: This paper will be published in IEEE Network

Published
2020

3. Popularity-Aware Service Provisioning Framework in Cloud Environment.

Author

Ko, Haneul, Kim, Yumi, Kim, Bokyeong, and Kyung, Yeunwoong

Subjects
DATA analytics, MARKOV processes, QUALITY of service, POPULARITY
Abstract

To balance the tradeoff between quality of service (QoS) and operating expenditure (OPEX), the service provider should request the appropriate amount of resources to the cloud operator based on the estimated variation of service requests. This paper proposes a popularity-aware service provisioning framework (PASPF), which leverages the network data analytics function (NWDAF) to obtain analytics on service popularity variations. These analytics estimate the congestion level and list of top services contributing most of the traffic change. Based on the analytics, PASPF enables the service provider to request the appropriate amount of resources for each service for the next time period to the cloud operator. To minimize the OPEX of the service provider while keeping the average response time of the services below their requirements, we formulate a constrained Markov decision process (CMDP) problem. The optimal stochastic policy can be obtained by converting the CMDP model into a linear programming (LP) model. Evaluation results demonstrate that the PASPF can achieve less than 50 % OPEX of the service provider compared to a popularity-non-aware scheme while keeping the average response time of the services below the requirement. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Handover in LTE-U/LAA

Author

Lee, Jaewook, Ko, Haneul, Pack, Sangheon, Shen, Xuemin (Sherman), editor, Lin, Xiaodong, editor, and Zhang, Kuan, editor

Published
2020
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13. Delayed Location Management in Network Mobility Environments

Author

Ko, Haneul, Pack, Sangheon, Lee, Jong-Hyouk, Petrescu, Alexandru, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Coulson, Geoffrey, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin Sherman, Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert Y., Series editor, Lee, Jong-Hyouk, editor, and Pack, Sangheon, editor

Published
2017
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19. Situation-Aware Cluster and Quantization Level Selection Algorithm for Fast Federated Learning

Author

Seo, Sangwon, Lee, Jaewook, Ko, Haneul, Pack, Sangheon, Seo, Sangwon, Lee, Jaewook, Ko, Haneul, and Pack, Sangheon

Abstract

In federated learning (FL), which clients and quantization levels are selected for the deep model parameters has a significant impact on learning time as well as learning accuracy. This is not a trivial issue because it is also significantly affected by factors, such as computational power, communication capacity, and data distribution. Considering these factors, we formulate a joint optimization problem for clustering and selecting clusters with quantization levels. Due to the high complexity of the formulated problem, we propose a situation-aware cluster and quantization level selection (SITUA-CQ) algorithm. In this algorithm, the FL server first assembles clients into clusters to mitigate the impact of biased data distributions and determines the most suitable clusters and quantization levels based on their computing power and channel quality. Extensive simulation results show that SITUA-CQ can reduce the round time by up to 80.3% compared to conventional algorithms., QC 20230824

Published
2023
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20. Location-Aware B5G LAN-Type Services: Architecture, Use Case, and Challenges

Author

Kyung, Yeunwoong, Ko, Haneul, Lee, Jaewook, Pack, Sangheon, Park, Noik, and Ko, Namseok

Abstract

5G LAN-type services are perceived as a key enabling technology for Industry 4.0 due to its local and private group communications comparable to local area networks and virtual private networks with improved 5G capabilities such as quality of service (QoS), mobility, and charging. However, in current 5G LAN-type services, user plane traffic goes through at least one session anchor point (i.e., user plane function (UPF)) even when users are in close proximity, which can significantly increase the end-to-end delay and network load. To address this issue, we propose location-aware beyond 5G (B5G) LAN-type services (LBLS) where the location information is evaluated and the optimal user plane path is established by means of UPF, 5G next-generation Node B (gNB), or nearby user equipment (UE) depending on the location. To enable the LBLS operation, we introduce functional extensions of the 5G control plane and devise user plane establishment procedures to configure the optimal anchor points. Numerical results demonstrate that LBLS can reduce the end-to-end delay by 87 percent compared to the conventional approach.

Published
2024
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