• 한국음향학회:학술대회논문집
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• 한국음향학회 1993년도 학술논문발표회 논문집 제12권 1호
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• pp.273-275
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• 1993

The throughput of conventional ARQ protocols can be improved by dynamically adapting the packet length. This protocol transmits packets with the length to maximize the transmission efficiency, based on the dynamic estimation of time-varying channel condition. A very simple adaptive scheme is presented. The results of a simulation show that the scheme performs well.

• 대한전자공학회논문지SD
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• 제48권2호
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• pp.28-34
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• 2011

본 논문에서는 H.264/AVC 인코더를 위한 하드웨어 지향 알고리즘의 정화소 및 부화소 움직임 예측 코어를 제안한다. 정화소 움직임 엔진의 경우 참조블록은 병렬 처리 내의 연속된 현재 블록들에 공유되어 데이터 재사용율을 높이고 오프칩 대역폭을 줄인다. 부화소 움직임 엔진의 경우 두 단계의 순차적 보간 신호 생성 대신 불필요한 후보 위치들 대신 1/2과 1/4 화소정밀도 신호를 병렬 기법으로 생성하여 처리량을 두배로 높인다. 또한 제안하는 H.264 움직임 예측 코어는 Chartered $0.18{\mu}m$ CMOS 1P5M 공정의 MPW(Multi-Project Wafer)를 통해 칩으로 제작되었으며 높은 처리량으로 HDTV 720p 30fps를 실시간 지원한다.

• 대한임베디드공학회논문지
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• 제7권3호
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• pp.129-134
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• 2012

The objective of cache is to reduce I/O access of physical storage device so that user accesses their data faster. Traditionally, the most important metric to measure the performance of cache is hitratio. Thus, when the cache maintains hitratio high, it is regarded as a good cache replacement policy. However, the cache miss latency is different when the storages are heterogeneous. Though the cache hitratio is high, if the cache often misses with low performance disk, then the user experiences low performance. To address this problem we proposed eviction cost estimation based cache management. In our result, the eviction cost estimation based cache management has 10~30% throughput improvement compared with LRU cache management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4259-4271
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• 2016

With the increased popularity of IEEE 802.11 WLAN, the density of the WLAN devices per access point has also increased, resulting in throughput performance degradation. One of the solutions to the problem is improving the protocol efficiency by a using multi-round contention scheme. This paper first discusses how to estimate the number of contending stations in a WLAN network by using minimum elapsed backoff counter values that can be easily monitored by each station. An approximate closed form expression is derived for the number of active contending stations using the smallest backoff counter value in the network. We then apply this result to adapt the number of contending rounds according to the network loading level to enhance the throughput performance of a multi-round contention scheme. Through simulation, we show that the accuracy of the estimation algorithm depends on the contention parameters of W and the number of backoff counter observing samples, and found a reasonable value for each parameter. We clearly show that our adaptive multi-round contention scheme outperforms the standard contention scheme that uses a fixed number of rounds.

• ETRI Journal
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• 제31권2호
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• pp.173-181
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• 2009

The growth of the World Wide Web and web-based applications is creating demand for high performance web servers to offer better throughput and shorter user-perceived latency. This demand leads to widely used cluster-based web servers in the Internet infrastructure. Load balancing algorithms play an important role in boosting the performance of cluster web servers. Previous load balancing algorithms suffer a significant performance drop under dynamic and database-driven workloads. We propose an estimation-based load balancing algorithm with admission control for cluster-based web servers. Because it is difficult to accurately determine the load of web servers, we propose an approximate policy. The algorithm classifies requests based on their service times and tracks the number of outstanding requests from each class in each web server node to dynamically estimate each web server load state. The available capacity of each web server is then computed and used for the load balancing and admission control decisions. The implementation results confirm that the proposed scheme improves both the mean response time and the throughput of clusters compared to rival load balancing algorithms and prevents clusters being overloaded even when request rates are beyond the cluster capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1301-1312
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• 2020

Using decode-and-forward relaying in the cognitive radio networks, the spectrum efficiency can improve furthermore. The optimization algorithm of the spectrum sensing estimation time is presented for the cognitive relay networks in this paper. The longer sensing time will bring two aspects of the consequences. On the one hand, the channel parameters are estimated more accurate so as to reduce the interferences to the authorized users and to improve the throughput of the cognitive users. On the other hand, it shortens the transmission time so as to decease the system throughput. In this time, it exists an optimal sensing time to maximize the throughput. The channel state information of the sub-bands is considered as the exponentially distributed, so a stochastic programming method is proposed to optimize the sensing time for the cognitive relay networks. The computer simulation results using the Matlab software show that the algorithm is effective, which has a certain engineering application value.

• 수산해양교육연구
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• 제29권2호
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• pp.354-364
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• 2017

This study tries to evaluate the effect of ITT introduction in Busan New Port. The study used the estimation model of the number of vehicles required in accordance with the backhaul rate. The model used big data, COPINO e-document for one year in 2015. COPINO recorded the event such as truck ID, container ID, ATA, damage etc when truck arrived at gate. The study finds important information to estimate the required number of trucks for handling current ITT containers in Busan New Port: Daily throughput in Busan New Port is 1650 vans, especially night throughput recorded peak level in 1800 hours to 2400 hours, the throughput between adjacent terminals recorded high, i.e PNIT to HPNT. The transportation capability for 6 hours between terminals is from 4 vans to 7 vans. The required trucks are estimated 89 currently without considering peak level. If we change the back haul rate from current 20% to 40%, 60% and 80%, how much would the cost drop? It was discovered that, if it is raised to 40%, 60% and 80%, the number of vehicle required will be reduced from 89 (current) to 76, 65 and 59. It was also discovered that the total savings will reduce down to 12%, 25% and 34%.

• Journal of Computing Science and Engineering
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• 제11권2호
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• pp.58-68
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• 2017

While graphics processing units (GPUs) can be used to improve the performance of real-time embedded applications that require high throughput, it is challenging to estimate the worst-case execution time (WCET) of GPU programs, because modern GPUs are designed for improving the average-case performance rather than time predictability. In this paper, a reordering framework is proposed to regulate the access to the GPU data cache, which helps to improve the accuracy of the estimation of GPU L1 data cache miss rate with low performance overhead. Also, with the improved cache miss rate estimation, tighter WCET estimations can be achieved for GPU programs.

• 전자공학회논문지SC
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• 제47권6호
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• pp.51-57
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• 2010

본 논문에서는 다중 안테나 시스템에서의 전송률과 안정성 측면에서의 최적의 성능을 발휘하기 위해 채널 추정오차에 강인한 적응형 다중입출력(MIMO) 스위칭 알고리즘을 제안한다. 제안된 논문은 무선 채널의 추정 오차에 대한 강인성을 확보하기 위하여 가변형 패킷오류 예측 방식에 기반을 두었으며, 기존의 MIMO 스위칭 방식에 비해 스펙트럼 효율이 약 8% 이상 증대 됨을 확인할 수 있었다.

• ETRI Journal
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• 제34권5호
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• pp.771-774
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• 2012

Typical channel allocation algorithms for secondary users do not include processes to reduce the frequency of switching from one channel to another caused by random interruptions by primary users, which results in high packet drops and delays. In this letter, with the purpose of decreasing the number of switches made between channels, we propose a nonparametric channel allocation algorithm that uses robust kernel density estimation to effectively schedule idle channel resources. Experiment and simulation results demonstrate that the proposed algorithm outperforms both random and parametric channel allocation algorithms in terms of throughput and packet drops.