• 정보과학회 논문지
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• 제44권3호
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• pp.223-231
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• 2017

본 논문에서는 최근 광범위하게 사용되고 있는 멀티 코어 환경에서의 모바일 장치의 성능에 대하여 연구하였다. 이전에 연구되어왔던 멀티 코어의 성능에 대한 분석은, 대부분 데스크톱 PC에서의 분석이었고, heterogeneous 멀티 코어에 대한 분석방법이 충분하지 않았다. 이러한 문제점을 보완하고자 homogeneous 멀티 코어의 분석 방법을 응용한 heterogeneous 멀티 코어 환경에서 성능을 분석하는 방법을 제안하였다. 본 연구에서는 이를 분석하는 데 있어서 작업의 할당에는 Size Interval Task Allocation (SITA) 기법을 사용하였고, 코어에서의 처리 방법은 Shortest Remaining Processing Time (SRPT) 기법을 사용하였다. 이 중 SITA 기법에서 가장 중요한 분석인 cutoff point에 대한 새로운 계산 방법을 제안하였고, 이를 체류 시간을 계산하는 데 사용함으로써 계산의 용이성과 정확성을 높였다. 또한, ESESC 시뮬레이터에서의 측정을 통해 분석값과 측정값에 큰 차이가 없음을 확인하였다.

• Journal of Information Processing Systems
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• 제19권2호
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• pp.240-257
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• 2023

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권6호
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• pp.2648-2668
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• 2016

Modern mobile devices are equipped with various accelerated processing units to handle computationally intensive applications; therefore, Open Computing Language (OpenCL) has been proposed to fully take advantage of the computational power in heterogeneous systems. This article introduces a parallel software decoder of Low Density Parity Check (LDPC) codes on an embedded heterogeneous platform using an OpenCL framework. The LDPC code is one of the most popular and strongest error correcting codes for mobile communication systems. Each step of LDPC decoding has different parallelization characteristics. In the proposed LDPC decoder, steps suitable for task-level parallelization are executed on the multi-core central processing unit (CPU), and steps suitable for data-level parallelization are processed by the graphics processing unit (GPU). To improve the performance of OpenCL kernels for LDPC decoding operations, explicit thread scheduling, vectorization, and effective data transfer techniques are applied. The proposed LDPC decoder achieves high performance and high power efficiency by using heterogeneous multi-core processors on a unified computing framework.

• IEIE Transactions on Smart Processing and Computing
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• 제5권4호
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• pp.289-293
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• 2016

As more mobile devices are equipped with multi-core CPUs and are required to execute many compute-intensive multimedia applications, it is important to optimize the systems, considering the underlying parallel hardware architecture. In this paper, we implement and optimize ray-tracing application tailored to a given mobile computing platform with multiple heterogeneous processing elements. In this paper, a lightweight ray-tracing application is specified and implemented in Kahn process network (KPN) model-of-computation, which is known to be suitable for the description of real-time applications. We take an open-source C/C++ implementation of ray-tracing and adapt it to KPN description in the Distributed Application Layer framework. Then, several possible configurations are evaluated in the target mobile computing platform (Exynos 5422), where eight heterogeneous ARM cores are integrated. We derive the optimal degree of parallelism and a suitable distribution of the replicated tasks tailored to the target architecture.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.101-104
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• 2007

Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

• 한국인터넷방송통신학회논문지
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• 제18권3호
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• pp.111-117
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• 2018

서로 다른 기능을 가진 코어들을 집적시킨 이기종 다중코어 환경은 더욱 복잡하고 다양해지는 임베디드 시스템의 요구사항들을 만족시키는 강력한 도구이며 특화된 응용을 위해 상이한 코어 상에서 별개의 운영체제를 수행하여 적합한 환경을 구성한다. 그러나 이런 이질성은 개발 환경을 더욱 복잡하게하고 프로그래밍을 어렵게 하며 개발과 디버깅을 쉽지 않도록 만든다. 본 논문에서는 이기종 다중코어 환경을 단일 다중코어 환경으로 매핑 가능함을 보이고 이기종 다중코어 환경에서 프로세스 간 통신에 사용하는 RPMsg를 리눅스 기반으로 구축하여 여러 단계의 개발과정을 축소할 수 있음을 보인다. 이러한 단순화를 통해 이기종 다중코어 환경에서의 개발 기간을 대폭 줄여줄 수 있는 시뮬레이션 방법을 제안한다.

• 한국통신학회논문지
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• 제38B권3호
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• pp.163-171
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• 2013

최근 HD급 동영상이나 3D 어플리케이션과 같은 이전보다 저사양, 모바일 단말에서는 구동하기 힘든 프로그램들에 대한 이용 요구가 확대되면서 처리해야 할 콘텐츠 데이터들이 고용량화 되고 있다. 클라우드 기반의 VDI(Virtual Desktop Infrastructure) 서비스는 이를 처리하기 위해 효율적인 데이터 처리 능력이 필요해졌으며 QoE(Quality of Experience) 보장을 위한 성능 개선 연구가 이슈가 되고 있다. 본 논문에서는 H/W 성능이 향상되어 CPU와 GPU를 탑재한 Thick Client기반의 3가지 Thick-Thin간 VDI 자원 공유 및 위임이 가능한 VDI 서비스에 대해 제안하며, VDI 서비스 성능의 개선을 위해 CPU와 GPU가 혼합된 Heterogeneous 멀티코어 환경에서 CPU와 GPU 병렬 처리 기법인 OpenMP와 CUDA를 활용하여 VDI 서비스 최적화 방안을 제안하고 기존의 VDI와 비교한 성능을 거론한다.

• 한국인터넷방송통신학회논문지
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• 제14권3호
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• pp.99-104
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• 2014

본 논문은 유무선융합망에서 스마트스크린 서비스를 효과적으로 제공하기 위하여 이기종 네트워크 환경의 멀티전송기법을 제시하였다. 유무선 융합 이종망 환경에서 다수 협업 장치간에 스마트 스크린 핸드오버 알고리즘과, AV 스트리밍과 파일의 스마트 스크린 서비스를 제공하는 NAS 장치와 서비스 관리 및 운영 시스템을 연구함으로써 이종망간 심리스 스마트 스크린 협업 서비스 호처리 엔진 및 이동성 관리, 멀티 사용자/멀티 스트림 지원하는 AV 스트리밍전송 서비스, 스마트 스크린 협업 서비스 등의 타당성을 제안하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권5호
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• pp.691-708
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• 2010

An important issue of supporting multi-users with diverse quality-of-service (QoS) requirements over wireless networks is how to optimize the systematic scheduling by intelligently utilizing the available network resource while, at the same time, to meet each communication service QoS requirement. In this work, we study the problem of a variety of communication services over multi-media heterogeneous cognitive OFDM system. We first divide the communication services into two parts. Multimedia applications such as broadband voice transmission and real-time video streaming are very delay-sensitive (DS) and need guaranteed throughput. On the other side, services like file transmission and email service are relatively delay tolerant (DT) so varying-rate transmission is acceptable. Then, we formulate the scheduling as a convex optimization problem, and propose low complexity distributed solutions by jointly considering channel assignment, bit allocation, and power allocation. Unlike prior works that do not care computational complexity. Furthermore, we propose the FAASA (Fairness Assured Adaptive Sub-carrier Allocation) algorithm for both DS and DT users, which is a dynamic sub-carrier allocation algorithm in order to maximize throughput while taking into account fairness. We provide extensive simulation results which demonstrate the effectiveness of our proposed schemes.

• Journal of Communications and Networks
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• 제18권2호
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• pp.150-161
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• 2016

Coordinated multi-point transmission (CoMP) techniques are being touted as enabling technologies for interference mitigation in next generation heterogeneous wireless networks (HetNets). In this paper, we present a comparative performance study of uplink (UL) CoMP algorithms for the 3GPP LTE HetNets. Focusing on a distributed and functionally-split architecture, we consider six distinct UL-CoMP algorithms: 1. Joint reception in the frequency-domain (JRFD) 2. Two-stage equalization (TSEQ) 3. Log-likelihood ratio exchange (LLR-E) 4. Symmetric TSEQ (S-TSEQ) 5. Transport block selection diversity (TBSD) 6. Coordinated scheduling with adaptive interference mitigation (CS-AIM) where JRFD, TSEQ, S-TSEQ, TBSD and CS-AIM are our main contributions in this paper, and quantify their relative performances via the post-processing signal-to-interference-plus-noise ratio distributions.We also compare the CoMP-specific front-haul rate requirements for all the schemes considered in this paper. Our results indicate that, with a linear minimum mean-square error receiver, the JRFD and TSEQ have identical performances, whereas S-TSEQ relaxes the front-haul latency requirements while approaching the performance of TSEQ. Furthermore, in a HetNet environment, we find that CS-AIM provides an attractive alternative to TBSD and LLR-E with a significantly reduced CoMP-specific front-haul rate requirement.