• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.2
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• pp.103-113
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• 2013

We analyze the queueing model for leaky bucket (LB) scheme with dynamic arrivals and token rates. In other words, in our LB scheme the arrivals and token rates are changed according to the buffer occupancy. In telecommunication networks, the LB scheme has been used as a policing function to prevent congestion. By considering bursty and correlated properties of input traffic, the arrivals are assumed to follow a Markov-modulated Poisson process (MMPP). We derive the distribution of system state, and obtain the loss probability and the mean waiting time. The analysis is done by using the embedded Markov chain and supplementary variable method. We also present some numerical examples to show the effect of our proposed model.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.7
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• pp.36-45
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• 1999

In order to control the flow of traffics in ATM networks and optimize the usage of network resources, an efficient control mechanism is necessary to cope with congestion and prevent the degradation of network performance caused by congestion. In this paper, Buffered Leaky Bucket which applies the same control scheme to a variety of traffics requiring the different QoS(Quality of Service) and Neural Networks lead to the effective buffer utilization and QoS enhancement in aspects of cell loss rate and mean transfer delay. And the cell scheduling algorithms such as DWRR and DWEDF for multiplexing the incoming traffics are enhanced to get the better fair delay. The network congestion information from cell scheduler is used to control the predicted traffic loss rate of Neural Leaky Bucket, and token generation rate and buffer threshold are changed by the predicted values. The prediction of traffic loss rate by neural networks can enhance efficiency in controlling the cell loss rate and cell transfer delay of next incoming cells and also be applied for other traffic controlling schemes. Computer simulation results performed for random cell generation and traffic prediction show that QoSs of the various kinds of traffcis are increased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1178-1190
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• 2009

IEEE 802.11e proposed by IEEE 802.11 working group to guarantee QoS has contention based EDCA and contention free based HCCA. HCCA, a centralized polling based mechanism of 802.11e, needs a scheduling algorithm to allocate the network resource efficiently. The existing standard scheduler, however, is inefficient to support for QoS guarantee for real-time service having VBR traffic. To efficiently assign resource for VBR traffic, in this paper, we propose TXOP algorithm based on dual leaky bucket using average resource allocation and peak resource allocation. The minimum TXOP of each station is obtained by using statistical approach to maximize number of stations of which performance satisfy QoS target. Simulation results show that the proposed algorithm has much higher performance compared with reference scheduler in terms of throughput and delay.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.4
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• pp.583-592
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• 1998

In this paper, the cell loss rate is analyzed in terms of the input traffic stream of different speed in ATM network. The cell loss rate is calculated by birth-death process of Leaky-Bucket mechanism as the representative algorithm of usage parameter control. The cell loss rate assumed 2-state MMPP input process to be birth-death process by considering the character of token pool about finite capacity queue. The results from numerical analysis show that the cell loss rate decreases abruptly according to the buffer size increase. The computer simulation by SIMSCRIPT II.5 has been done and compared with on/off input source case to verify the analysis results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.2828-2835
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• 1996

In this paper we propose a new shaping algorithm which can control the shaping delay and the output buffer size based on the leaky bucket counter with a threshold value. This paper assumes that input traffic of the proposed shaping algorithm is the worst case traffic tolerated by the continuous leaky bucket algorithm and claracterizes traffic patterns that can depart from our shaping algorithm. We also compare shaping delay and output buffer size of the proposed algorithm with the existing shaping algorithm without a threshold value. Our results show that the proposed shaping algorithm can easily manage the shaping delay and output buffer size than any other mechanism.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.895-900
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• 2010

As the diverse telecommunication services have been developed, network designers need to prevent congestion which may be caused by properties of timecorrelation and burstiness, and unpredictable statistical fluctuation of traffic streams. This paper considers the leaky bucket scheme with combined control of arrival and token rates, in which the arrival rate and the token generation interval are controlled according to the queue length. By using the embedded Markov chain and the supplementary variable methods, we obtain the queue length distribution as well as the loss probability and the mean waiting time.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2779-2789
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• 1999

In this paper, we propose a new neural Buffered Leaky Bucket algorithm for preventing the degradation of network performance caused by congestion and dealing with the traffic congestion in ATM networks. We networks. We justify the validity of the suggested method through performance comparison in aspects of cell loss rate and mean transfer delay under a variety of traffic conditions requiring the different QoS(Quality of Service). also, the cell scheduling algorithms such as DWRR and DWEDF used for multiplexing the incoming traffics are induced to get the delay time of the traffics fairly. The network congestion information from cell scheduler is used to control the predicted traffic loss rate of Neural Leaky Bucket, and token generation rate is changed by the predicted values. The prediction of traffic loss rate by neural networks can effectively reduce the cell loss rate and the cell transfer delay of next incoming cells and be applied to other traffic control systems. Computer simulation results performed for traffic prediction show that QoSs of the various kinds of traffics are increased.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.472-474
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• 2000

본 논문은 VOD 시스템에서 QoS를 보장해 주기 위한 흐름 제어 기법을 제안하고 실제 구현된 VOD 시스템에서 제안된 알고리즘을 적용하고 성능을 측정하였다. 기존의 버퍼를 관리하는 Leaky Bucket 알고리즘과 패킷의 손실률에 기반한 네트워크의 상태를 동시에 고려해서 클라이언트와 서버간에 전송 속도를 제어한다. 즉, 시간에 따라 변화하는 네트워크의 상태를 클라이너트 버퍼 관리에 반영해줌으로써 클라이언트 버퍼의 오버플로우 및 언더 플로우를 방지하고 QoS를 보장한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.327-330
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• 2011

본 논문에서는 ATM network에서 트래픽 제어를 위하여 리키버켓과 EWMA로 구성된 셀 간격 제어기를 연구한다. 제안하는 알고리즘은 토큰 풀을 가진 리키버켓과 시간 윈도우를 가진 EWMA, 간격제어 버퍼로 구성된다. BONeS 시뮬레이터에서 ON/OFF 트래픽 소스 모델을 이용하여 제안한 UPC 알고리즘의 성능을 평가한 결과, 패킷화된 음성 트래픽과 고속 트래픽 소스 모두 셀 간격이 평균 비트율에 수렴하여 제어되는 것을 관찰할 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5A
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• pp.370-375
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• 2005

While the international standards bodies recommend the dual leaky buckets for the traffic specification for VBR service, video traffic shows burstiness in multiple time-scales. In order to fill this gap between the current standards and real traffic characteristics, we present a standard-compatible traffic parameter selection method based on the notion of a critical time scale (CTS). Since the defined algorithm minimizes the required link capacity under a maximum delay constraint, it could be used as a benchmark even when it can not be implemented easily. Simulation results with compressed video traces demonstrate the efficiency of the defined traffic parameter selection algorithm in resource allocation.