Browsing by Author "Hah, JM"

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A delay and loss versatile scheduling discipline in ATM switches
(1998-01-01)
Hah, JM
;
Yuang, MC
;
資訊工程學系
;
Department of Computer Science
In this paper, we propose a versatile scheduling discipline, called Precedence with Partial Push-out (PPP), in Asynchronous Transfer Mode (ATM) switches supporting two delay and two loss priorities. By employing a threshold L, PPP provides delay guarantee by allowing a newly-arriving high-delay-priority cell to precede a maximum of L low-delay-priority cells. Through the use of another threshold R, the discipline offers loss guarantee by permitting a newly-arriving high-loss-priority cell to push out the last low-loss-priority cell located beyond the Rth location in a full queue. By setting L and R properly, PPP versatilely performs as any one of the four widely-accepted disciplines, namely the FCFS, head-of-line, push-out, or head-of-line with push-out disciplines. To determine L and R retaining demanded Quality of Services (QoSs), we provide an in-depth queueing analysis for the Cell Delay (CD) and Cell Loss Ratio (CLR) of high-delay-priority, low-loss-priority cells. We further propose a simple, algebra-based analysis for the CD and CLR for low-delay-priority, high-loss-priority cells. On the basis of these analyses, L and R can be dynamically and effectively adjusted to provide adequate delay and loss guarantees for high-priority cells while incurring only minimal performance degradation for other classes of cells. Finally, the paper presents simulation results confirming the accuracy of the analyses.
A delay and loss versatile scheduling discipline in ATM switches
(1998-03-01)
Hah, JM
;
Yuang, MC
;
資訊工程學系
;
Department of Computer Science
In this paper, we propose a versatile scheduling discipline, called Precedence with Partial Push-out (PPP), in Asynchronous Transfer Mode (ATM) switches supporting two delay sand two loss priorities. By employing a threshold L, the PPP discipline provides delay guarantee by allowing a newly-arriving high-delay-priority cell to precede a maximum of L, few-delay-priority cells. Through the use of another threshold R, the discipline offers loss guarantee by permitting a newly-arriving high-loss-priority cell to push out the last low-loss-priority cell located beyond the R-th location in a full queue. By setting L and R properly, PPP versatilely performs as any one of the four widely-accepted disciplines, namely, the FCFS, head-of-line, push-out, or head-of-line with push-out disciplines. For precisely determining L and R retaining demanded Quality of Services (QoSs), we provide an in-depth queueing analysis for the Cell Delay (CD) and Cell Loss Ratio (CLR) of high-delay-priority, low-loss-priority cells. We further propose a simple, algebra-based analysis for the CD and CLR of low-delay-priority, high-loss-priority cells. On the basis of these analyses, L and R can be dynamically and effectively adjusted to provide adequate delay and loss guarantees for high-priority cells while incurring only minimal performance degradation for other classes of cells. Finally, the paper presents simulation results confirming the accuracy of the analyses.
Estimation-based call admission control with delay and loss guarantees in ATM networks
(1996)
Hah, JM
;
Yuang, MC
;
資訊工程學系
;
Department of Computer Science
Estimation-based call admission control with delay and loss guarantees in ATM networks
(1997-04-01)
Hah, JM
;
Yuang, MC
;
交大名義發表
;
資訊工程學系
;
National Chiao Tung University
Call admission control (CAC) has been accepted as a potential solution for supporting a variety of traffic sources demanding different quality of service guarantees in asynchronous transfer mode networks. Basically, CAC is required to consume a minimum of time and space to make call acceptance decisions. In the paper a CAC algorithm is presented based on a novel estimation method, called quasilinear dual-class correlation (QLDC). All heterogeneous traffic calls are initially categorised into various classes. According to the number of calls in each traffic class, QLDC conservatively and precisely estimates the cell delay and cell loss ratio for each traffic class via simple vector multiplication. These vectors are computed in advance from the results of three dual arrival queuing models, M-[N1] + I-[N2]/D/1/K, M-1([N1]) + M-2([N2])/D/1/K and I-1([N1]) + I-2([N2)]/D/1/K, where M and I represent the Bernoulli process and the interrupted Bernoulli process, respectively. Consequently, the authors' QLDC-based CAC, as will be shown, yields low time complexity O(C) (in vector multiplications) and space complexity O(WC2) (in bytes), where C is the total number of traffic classes and W is the total number of aggregate load levels. Numerical examples are also employed to justify that QLDC-based estimated results profoundly agree with simulation results in both the single-node and end-to-end cases.
Neural-network-based call admission control in ATM networks with heterogeneous arrivals
(1997-09-08)
Hah, JM
;
Tien, PL
;
Yuang, MC
;
交大名義發表
;
資訊工程學系
Call Admission Control (CAC) has been accepted as a potential solution for supporting diverse, heterogeneous traffic sources demanding different Quality of Services (QOSs) in ATM networks. Also, CAC is required to consume a minimum of time and space to make call acceptance decisions. In this paper, we present an efficient neutral-network-based CAC (NNCAC) mechanism for ATM networks with heterogeneous arrivals. All heterogeneous traffic calls are initially categorized into various classes. Based an the number of calls in each class, NNCAC efficiently and accurately estimates the cell delay and cell loss ratio of each class in real time by means of a pre-trained neutral network. According to our decent study which exhibits the superiority of the employment of analysis-based training data over simulation-based data, we particularly construct the training data from a heterogeneous-arrival dual-class queueing model M-[N1] + I-[N2]/D/1/K, where M and I represent the Bernoulli and interrupted Bernoulli processes, and N-1 and N-2 represent the corresponding numbers of calls, respectively. Analytic results of the queueing model are confirmed by simulation results. Finally, we demonstrate the profound agreement of our neural-network-based estimated results with analytic results, justifying the viability of our NNCAC mechanism. (C) 1997 Elsevier Science B.V.