• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.97-99
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• 2021

Edge caching can provide high QoE by reducing traffic in the backhaul network and reducing latency in video streaming services. But due to the limited capacity of edge cache, large amounts of content cannot be cached. In this paper, we propose an edge-fog prefix caching that reduces playback delay by caching prefixes of video content on edges and storing the rest in fog cache.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.47-52
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• 2023

Mobile Edge Computing(MEC) is considered as a promising technology to effectively support the explosively increasing traffic demands. It can provide low-latency services and reduce network traffic by caching contents at the edge of networks such as Base Station(BS). Although users may associate with the nearest BSs, it is more beneficial to associate users to the BS where the requested content is cached to reduce content download latency. Therefore, in this paper, we propose a mobility-aware joint caching and user association algorithm to imporve the cache hit ratio. In particular, the proposed algorithm performs caching and user association based on sojourn time and content preferences. Simulation results show that the proposed scheme improves the performance in terms of cache hit ratio and latency as compared with existing schemes.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.43-50
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• 2022

As the use of mobile data increases, the proportion of video content is increasing steeply. In order to solve problems that arise when mobile users receive data from geographically remote cloud servers, methods of caching data in advance to edge servers geographically close to the users are attracting lots of attention. In this paper, we present a caching policy that stores data on Small Cell Base Station(SBS) to effectively provide content files to mobile users by applying a delayed offloading scheme in a cellular network. The goal of the proposed policy is to minimize the size of data transmitted from Macro Base Station(MBS) because the delayed offloading scheme requires more cost than when downloaded from MBS than from SBS. The caching policy is proposed to determine the size of content file and which content file to be cached to SBS using the probability of mobile users' paths and the popularity of content files, and to replace content files in consideration of the overlapping coverage of SBS. In addition, through performance evaluation, it has been proven that the proposed policy reduces the size of data downloaded from MBS compared to other algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.135-137
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• 2022

이동성 기반의 기존 엣지 캐싱 연구에서는 인기도가 짧은 시간 급격하게 변화하는 SNM(Shot Noise Model) 콘텐츠를 반영하지 않았다. 동적 인기도 특성을 다루지 않는 경우, 잦은 캐시 미스가 발생하므로 SNM 콘텐츠를 고려하는 것은 중요하다. 이에 본 논문은 이동성을 고려한 기존 연구에 SNM 콘텐츠를 함께 고려하고, 시뮬레이션을 통해 기존 연구 대비 제안 알고리즘의 향상된 캐시 적중률을 확인한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.165-166
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• 2022

본 논문에서는 웹툰 플랫폼 서비스를 위한 모바일 엣지 컴퓨팅의 구조를 제안한다. 웹툰과 같이 모바일 디바이스에서 실행되는 데이터들을 클라우드 서버로 오프로드하거나 원격 서버로부터 필요한 응용프로그램들을 다운로드 받지 않고, 모바일과 가까운 곳에 캐싱 콘텐츠를 전개함으로써 전송 지연없는 서비스를 보장받으며, 데이터가 발생한 근접 지역에서 데이터 분석 및 처리가 가능하므로 딥러닝을 적용한 새로운 서비스 카테고리로 확장할 수 있음을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.110-113
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• 2022

인터넷을 통해 주위 사물과 연결된 차량은 사용자에게 편리성을 제공하기 위해 다양한 콘텐츠를 요구하는데 클라우드로부터 가져오는 시간이 비교적 오래 걸리기 때문에 차량과 물리적으로 가까운 위치에 캐싱하는 기법들이 등장하고 있다. 본 논문에서는 기반 시설이 밀집하게 설치된 도시 환경에서 maximum distance separable(MDS) 코딩을 사용해 road side unit(RSU)에 캐싱하는 방법에 대해 연구하였다. RSU의 중복된 서비스 커버리지 지역을 고려하여 차량의 콘텐츠 요구에 대한 RSU hit ratio를 높이기 위해 deep Q-learning(DQN)를 사용하였다. 실험 결과 비교 알고리즘보다 hit raito 측면에서 더 높은 성능을 보이는 것을 증명하였다.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.7
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• pp.167-176
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• 2019

Recently, as the types of services that can be enjoyed in mobile telecommunication networks such as social networks and video streaming are increasing, mobile users(MUs) can access mobile contents easily by consuming mobile data. However, under a mobile telecommunication environment, MUs have to pay a high data fee to a network service provider(SP) in order to enjoy contents. The 'data sponsor' technique, introduced as a way to solve this problem, has attracted attention as a breakthrough method for enhancing contents accessibility of MUs. In this paper, we propose an algorithm that determines the optimal discount rate through the Stackelberg game in the data sponsor environment. We also propose an algorithm to design edge caching, which caches highly popular content for MUs on edge server, through many-to-many matching game. Simulation results clearly indicate that the profit for CP's content consumption is improved by about 6~11%, and the profit of CP according to the ratio of edge caching is improved by about 12% than the other existing schemes under data sponsor environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1009-1019
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• 2017

Mobile Edge Computing(MEC) is a emerging technology to cope with mobile traffic explosion and to provide a variety of services having specific requirements by means of running some functions at mobile edge nodes directly. For instance, caching function can be executed in order to offload mobile traffics, and safety services using real time video analytics can be delivered to users. So far, a myriad of methods and architectures for personalized service recommendation have been proposed, but there is no study on the subject which takes unique characteristics of mobile edge computing into account. To provide personalized services, acquiring users' context is of great significance. If the conventional personalized service model, which is server-side oriented, is applied to the mobile edge computing scheme, it may cause context isolation and privacy issues more severely. There are some advantages at mobile edge node with respect to context acquisition. Another notable characteristic at MEC scheme is that interaction between users and applications is very dynamic due to temporal relation. This paper proposes the local service recommendation platform architecture which encompasses these characteristics, and also discusses the personalized service recommendation mechanism to be able to mitigate context isolation problem and privacy issues.