Interaction of call blocking and cell loss in an ATM network

Beshai, M.; Kositpaiboon, R.; Yan, James

doi:10.1109/49.310962

Cited by 15 publications

(3 citation statements)

References 3 publications

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“…Sensitivity of the maximum feasible call request rate to buffer size Using the parameters of Table I and a given buffer size, we repeatedly solved the LP of Section 2.5 for a range of call request rates. Comparing the call blocking probabilities obtained to the QoS constraint, p call ; we arrived at the maximum feasible call request rate, l n ; for which there exists a CAC policy satisfying both packet and call level QoS requirements (see (2)), for a buffer Figure 1. Note from Figure 1 that, at least over the small range of buffer sizes for which we computed LP solutions, a small increase of the buffer size dramatically increases the maximum feasible call request rate, l n : From these results, we can conclude that the consideration of buffers in modelling and analyzing the switch performance can make a significant difference.…”

Section: Optimal Policy and Effect Of Bufferingmentioning

confidence: 99%

Optimal call admission control under packet and call level QoS constraints and effect of buffering

Spitler

Lee

2003

Int J Communication

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SUMMARYFor a single network switch allocating link bandwidth to connections of a single class, an optimal call admission control (CAC) policy is found by the solution of a linear programming (LP) problem. Our optimization differs from previous work in that we include the effect of an output buffer in the switch for the temporary storage of packets bound for transmittal across the link. We find a policy that is optimal in the sense of minimizing call blocking subject to a packet level quality of service (QoS) requirement that limits the packet loss ratio. Such a policy's call blocking probability, if it is small enough to satisfy a call level QoS requirement, then establishes the feasibility of satisfying both the packet and call level QoS requirements for a given call request rate. We show with a previously described example that the addition of even a small output buffer can significantly increase the range of call request rates for which there exists a feasible policy, i.e. one that satisfies both QoS requirements. Also presented is an upper bound, valid for any fixed buffer size, on the range of call request rates for which there exists a feasible CAC policy.

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Section: Optimal Policy and Effect Of Bufferingmentioning

confidence: 99%

Optimal call admission control under packet and call level QoS constraints and effect of buffering

Spitler

Lee

2003

Int J Communication

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“…There is a substantial literature in this area (see [13], [21], [11], [23] and references therein). With very few exceptions, such as [4] and [11], the published work has focused on cell level QoS, such as cell loss ratio, cell delay and cell delay variation. Most CAC schemes are based on the well-known concept of effective bandwidth, which has been studied extensively (see [3], [6], [10], [14]).…”

Section: Introductionmentioning

confidence: 99%

Robust dynamic admission control for unified cell and call QoS in statistical multiplexers

Mitra¹,

Reiman²,

Wang

1998

IEEE J. Select. Areas Commun.

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The design of connection admission control (CAC) for a simple Markovian model of a multiservice statistical multiplexer is considered. The paper begins by laying the foundation through several fundamental analytic concepts, such as a semi-Markov decision process formulation of the design problem and time scale decomposition, before progressively leading up to real-world requirements, like robustness and simplicity of design. Several numerical illustrations are given. The salient contributions of the paper are as follows. 1) A unified treatment of multiclass cell and call QoS. 2) A CAC design which is robust, fair, and efficient. 3) Simplicity in the CAC design, together with an evaluation of the tradeoff with performance. 4) An analytic technique for computing the feasibility region in the space of call arrival rates where some control exists to satisfy QoS. 5) The discovery of near linearity of the boundary of the feasible region, which is then used to decompose the design problem. 6) A unified treatment of aggressive and conservative forms of CAC, the latter being conventional and the former yielding better call level performance. 7) An effective bandwidth definition based on the aggressive form of CAC, which influences the CAC design. 8) Demonstration of the beneficial impact on performance of cell level control. 9) An asymptotic theory of the joint behavior of cell loss and call blocking. 10) A rigorous development of time scale decomposition. 11) A numerical evaluation of the accuracy of the notion of nearly completely decomposable Markov chains.

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“…In reality, however, the number of calls being multiplexed is not fixed but forms the call-level process which is subject to blocking. Little work has appeared on the inclusion of the call-level process in admission control and bandwidth allocation at an ATM multiplexor [4]. In this paper we study admission control at an ATM multiplexor with call blocking and cell loss.…”

Section: : Introductionmentioning

confidence: 99%

Cell loss and call blocking at an ATM multiplexor

Kraimeche

Proceedings 7th International Conference on Computer Communications and Networks (Cat. No.98EX226)

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We study an ATM access node which multiplexes on-off calls onto a common channel on a cell loss and call blocking basis. Calls arrive at a Poisson rate , I calls/sec and require an exponentially distributed holding time of mean l / p seconds. When on, a call generates traffic at a fluid rate R cells/sec and when off it generates no traffic. The on and off time intervals are exponentially distributed with means l/a and l / p seconds, respectively. When arriving cells can 't be transmitted immediately, they are queued in a common buffer of size B cells. Cells arriving when the buffer is f u l l are assumed lost. Using a fluid model, we derive the cell loss and call blocking probabilities and apply them to provision the maximum call handling capacity, N, of the system. When N calls are already in progress, arriving calls are blocked.When call-level transition rates are much smaller than cell-level transitions, the input process is nearlycompletely decomposable (NCD). This NCD approximation greatly reduces the computational difficulty of the exact fluid model. Numerical results show that the NCD approximation is quite accurate over a wide range of traffic parameters.

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Interaction of call blocking and cell loss in an ATM network

Cited by 15 publications

References 3 publications

Optimal call admission control under packet and call level QoS constraints and effect of buffering

Optimal call admission control under packet and call level QoS constraints and effect of buffering

Robust dynamic admission control for unified cell and call QoS in statistical multiplexers

Cell loss and call blocking at an ATM multiplexor

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