• Title/Summary/Keyword: Throughput estimation

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ARQ Performance Analysis of Adaptive Packet Lenth Allocation Method (적응 패킷 길이 할당 방식의 ARQ 성능분석)

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    • Proceedings of the Acoustical Society of Korea Conference
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    • 1993.06a
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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.

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A Low Memory Bandwidth Motion Estimation Core for H.264/AVC Encoder Based on Parallel Current MB Processing (병렬처리 기반의 H.264/AVC 인코더를 위한 저 메모리 대역폭 움직임 예측 코어설계)

  • Kim, Shi-Hye;Choi, Jun-Rim
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.48 no.2
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    • pp.28-34
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    • 2011
  • In this paper, we present integer and fractional motion estimation IP for H.264/AVC encoder by hardware-oriented algorithm. In integer motion engine, the reference block is used to share for consecutive current macro blocks in parallel processing which exploits data reusability and reduces off-chip bandwidth. In fractional motion engine, instead of two-step sequential refinement, half and quarter pel are processed in parallel manner in order to discard unnecessary candidate positions and double throughput. The H.264/AVC motion estimation chip is fabricated on a MPW(Multi-Project Wafer) chip using the chartered $0.18{\mu}m$ standard CMOS 1P5M technology and achieves high throughput supporting HDTV 720p 30 fps.

A Cache Management Technique Based on Eviction Cost Estimation for Heterogeneous Storage Devices (이기종 저장장치를 위한 제거 비용 평가 기반 캐시 관리 기법)

  • Park, SeJin;Park, ChanIk
    • IEMEK Journal of Embedded Systems and Applications
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    • v.7 no.3
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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.

Statistical Estimation of the Number of Contending Stations and its Application to a Multi-round Contention Resolution Scheme

  • Jang, Seowoo;Choi, Jin-Ghoo;Yoon, Sung-Guk
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.9
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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.

Estimation-Based Load-Balancing with Admission Control for Cluster Web Servers

  • Sharifian, Saeed;Motamedi, Seyed Ahmad;Akbari, Mohammad Kazem
    • ETRI Journal
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    • v.31 no.2
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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.

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Optimization Algorithm for Spectrum Sensing Delay Time in Cognitive Radio Networks Using Decoding Forward Relay

  • Xia, Kaili;Jiang, Xianyang;Yao, Yingbiao;Tang, Xianghong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.3
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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.

The Evaluation of Backhaul Transport with ITT Platform - The Case of Busan New Port - (ITT Platform의 복화율 개선에 따른 효과 분석 - 부산항 신항을 대상으로 -)

  • PARK, Nam-Kyu;LEE, Jung-Hun
    • Journal of Fisheries and Marine Sciences Education
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    • v.29 no.2
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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%.

Warp-Based Load/Store Reordering to Improve GPU Time Predictability

  • Huangfu, Yijie;Zhang, Wei
    • Journal of Computing Science and Engineering
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    • v.11 no.2
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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.

Adaptive MIMO Switching Algorithm Robust for Channel Estimation Error (채널추정 오차에 강인한 적응형 MIMO 신호처리 기법)

  • Choi, Joon-Sung;Eun, Chang-Soo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.6
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    • pp.51-57
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    • 2010
  • In this paper, we propose a new adaptive MIMO switching algorithm that provides the optimal trade-off between throughput and reliability of data in MIMO system. The proposed algorithm is based on the variable packet error predictor which is robust for channel estimation error, and we show that our algorithm has a better spectrum efficiency than the conventional MIMO switching techniques about 8 percent point.

Distributed Channel Allocation Using Kernel Density Estimation in Cognitive Radio Networks

  • Ahmed, M. Ejaz;Kim, Joo Seuk;Mao, Runkun;Song, Ju Bin;Li, Husheng
    • ETRI Journal
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    • v.34 no.5
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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.