Modelling Deterministic Queues: The Leaky Bucket as an Arrival Process

Worster, Tom

doi:10.1016/b978-0-444-82031-0.50064-0

Cited by 14 publications

(13 citation statements)

References 1 publication

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“…The worst admissible behavior of a source that is specified by sustainable and peak rates and an intrinsic burst tolerance is an on-off behavior, transmitting fibt seconds at peak rate followed by an idle period of fibt(T.brlT per -1) seconds [13].…”

Section: Source Parametersmentioning

confidence: 99%

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On the efficiency of statistical—bitrate service for video

Karlsson

1998

Performance of Information and Communication Systems

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The provisioning of quality of service by means of statistical multiplexing has been an alluring research idea for the last decade of teletraffic research. In this paper we question the efficiency of statistical bitrate service which is the standardized representation of this operational mode for ATM networks. Our argument is that the amount of information needed about a traffic source in order to· attain a fair multiplexing gain is beyond what is captured in the standard's three-parameter traffic descriptor.

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Section: Source Parametersmentioning

confidence: 99%

“…For the leaky-bucket characterized source, one cannot justify any helpful assumptions about the variations within the bounds and an on-off pattern must consequently be assumed to be safe (even though such behavior is not observed for variable bit rate video) [13]. Following Hamdi et at.…”

Section: Comparison Of Efficiencymentioning

confidence: 99%

On the efficiency of statistical—bitrate service for video

Karlsson

1998

Performance of Information and Communication Systems

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“…It is a common belief that on-off sources are the worst case of independent, leaky bucket constrained sources, as in (Kositpaiboon and Phung 1990), (Rathgeb 1991), (Kvols and Blaabjerg 1992), (Worster 1994), (Johri 1995), (Elwalid, Mitra and Wentworth 1995) and (Presti, Zhang, Kurose and Towsley 1997). This is due to the fact that on-off patterns have the highest variance of all possible patterns and because of the assumption that a higher variance always leads to a higher loss rate.…”

Section: Existing Workmentioning

confidence: 99%

“…However, (Doshi 1994) and (Yamanaka, Sato and Sato 1992) have shown counter examples where a pattern called tri-state pattern results in more loss. In (Worster 1994) the author points to some possible flaws in (Yamanaka et al 1992) and tries to re-establish that on-off patterns are the worst case.…”

Section: Existing Workmentioning

confidence: 99%

Worst Case Arrivals of Leaky Bucket Constrained Sources: The Myth of the On-Off source

Oechslin

1997

Building QoS Into Distributed Systems

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We have simulated a set of independent connections limited by leaky bucket shapers and fed into a buffered multiplexer. This scenario is typical of an ATM switch or in a looser sense of an RSVP capable router. We found periodic traffic patterns which result in much worse loss rates than the on-off or tristate patterns found in literature to date. We give an intuitive justification for what we believe is the worst case and back this with an extensive set of simulations. Our results are important for Connection Acceptance Control when connections are known to be statistically independent. They clearly invalidate the widespread belief that on-off patterns are the worst case traffic of independent leaky bucket constrained sources.

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“…C L(x) = b(2p)(T on ; x) ; (T on ; x ; 1=p)r + ( p + R ; r)(x) ; Bc (4) To calculate the cell loss ratio we a l l o w x to vary over all phase possibilities and then divide by the number of combinations and also divide by the number of cells transmitted by both sources. The number of cells transmitted by both sources will be 2RT and the number of phase combinations will be T , so the cell loss ratio, C L R , is given by Equation 5.…”

Section: New Approach To Cell Lossmentioning

confidence: 99%

On worst case traffic in ATM networks

Erimli

Murphy²

1995

IEE Colloquium: Twelfth UK Teletraffic Symposium Performance Engineering in Telecommunications Networks

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Asynchronous Transfer Mode ( ATM ) networks, which are the emerging standards for the future broadband-ISDN networks, allows for the input tra c from users to vary both from one call to another and within the call. ATM speci es a method for controlling the tra c ow across the user network interface ( UNI ). This involves each user negotiating call parameters with the network. Once these parameters have been decided then a contract is made between the user and network. The network must then enforce the contract in order to guarantee performance and quality of service to other users. What is of interest to the network is given a particular set of users and contracts what is the worst tra c that the users could input to the network while still abiding by their contracts. This type of input tra c would be called the worst case tra c as it would produce the lowest performance in the network. The reason why this is of importance is that for simulating network performance we w ould like t o h a ve the worst case tra c inputs. Furthermore, it's important for the tra c controller, network, to know the possible worst case tra c so that it can assign parameters accordingly. The contract parameters have been decided upon by the standards organisations and what is needed now is to decide what type of tra c can pass these tests and produce the lowest network performance. This problem has been studied in the literature. We g i v e some theoretical background to explain some of the results in the litrature, and we further look at some examples of types of worst case tra c sources. We show that for the two most common types, the greedy on{o and the three state source that either can be worse, depending on the situation. This would imply that there is no general worst case tra c as has been considered for the last number of years.

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Modelling Deterministic Queues: The Leaky Bucket as an Arrival Process

Cited by 14 publications

References 1 publication

On the efficiency of statistical—bitrate service for video

On the efficiency of statistical—bitrate service for video

Worst Case Arrivals of Leaky Bucket Constrained Sources: The Myth of the On-Off source

On worst case traffic in ATM networks

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