On the 95-Percentile Billing Method

Dimitropoulos, Xenofontas; Hurley, Paul; Kind, Andreas; Stoecklin, Marc Ph.

doi:10.1007/978-3-642-00975-4_21

Cited by 56 publications

(59 citation statements)

References 1 publication

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“…Norton discussed 95 th percentile pricing in his white papers, particularly the possibility of ISPs gaming the scheme to get free transit [12], and the impact of streaming video on the statistics of customer traffic [13]. Dmitropoulos et al [2] studied the 95 th percentile billing method using traffic traces, and investigated how the 95 th percentile computed for a given network depends on factors such as the averaging window size and the effect of flow aggregation. In the context of broadband users, Stanojevic et al [10] used the Shapley value approach to quantify the contribution of each broadband user to the total costs of the access provider.…”

Section: Related Workmentioning

confidence: 99%

“…The industry standard for transit billing is the 95 th percentile billing method [1,2] wherein a transit provider measures the utilization of a customer link in 5-minute bins over the duration of a month, and then computes the 95 th percentile of these utilization values as the billing volume. The 95 th percentile method has several attractive properties.…”

Section: Introductionmentioning

confidence: 99%

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Volume-Based Transit Pricing: Is 95 the Right Percentile?

Raja

Dhamdhere²,

Scicchitano

et al. 2014

Passive and Active Measurement

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Abstract. The 95th percentile billing mechanism has been an industry de facto standard for transit providers for well over a decade. While the simplicity of the scheme makes it attractive as a billing mechanism, dramatic evolution in traffic patterns, associated interconnection practices and industry structure over the last two decades motivates an obvious question: is it still appropriate? In this paper, we evaluate the 95 th percentile pricing mechanism from the perspective of transit providers, using a decade of traffic statistics from SWITCH (a large research/academic network), and more recent traffic statistics from 3 Internet Exchange Points (IXPs). We find that over time, heavy-inbound and heavy-hitter networks are able to achieve a lower 95th-to-average ratio than heavy-inbound and moderate-hitter networks, possibly due to their ability to better manage their traffic profile. The 95 th percentile traffic volume also does not necessarily reflect the cost burden to the provider, motivating our exploration of an alternative metric that better captures the costs imposed on a network. We define the provision ratio for a customer, which captures its contribution to the provider's peak load.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Volume-Based Transit Pricing: Is 95 the Right Percentile?

Raja

Dhamdhere²,

Scicchitano

et al. 2014

Passive and Active Measurement

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show abstract

“…A common approach for transit ISPs is to charge the access ISPs based on the traffic volume. On the other hand, the 95th percentile method is an increasingly popular pricing policy used by network providers for billing lower-Tier ISPs [31], intending to avoid traffic bursts. Authors in [32] study top-percentile pricing schemes by considering a multihomed ISP seeking an efficient routing strategy to reduce his costs, while in our paper the ISP intends to solve a profitmaximization problem.…”

Section: Related Workmentioning

confidence: 99%

“…The second more interesting scenario assumes that the transit ISP charges based on the 95th percentile rule, which is a widely used approach to estimate the usage level of resources for long timescales (i.e. a month) [31]. This charging method penalizes traffic which has the same total volume but it is more bursty (variable).…”

Section: Game Theoretic Analysismentioning

confidence: 99%

Economic incentives for adopting congestion accountability protocols

Κωστόπουλος

Dimakis

Courcoubetis

2014

2014 26th International Teletraffic Congress (ITC)

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Abstract-New Internet protocols such as ECN, re-ECN and Conex, provide valuable information to ISPs about the congestion within a network. Such information could be useful in allocating network resources more equitably, as well as to employ new pricing schemes. However, in designing a new protocol one must take proper account of the incentive issues that thereby arise for its adoption. In this paper, we consider a duopoly market consisting of two access ISPs and formulate a noncooperative game over their choices of pricing strategies when one of them uses volume-based and the other congestionbased pricing. We prove, under mild conditions, the existence of a pure strategy Nash equilibrium for the competing providers. We further examine how the different types of transit charges affect the pricing strategies of the access ISPs. We find cases where the volume charging ISP is forced to leave the access market. We conclude that ISPs have economic incentives to adopt congestion accountability mechanisms, since they become more competitive due to the smoother and more predictable traffic they have to accommodate and to the lower transit charges they incur.

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“…The industry standard for determining the billing volume is the 95 th percentile method [4,5]: a transit provider measures the utilization of a customer link in 5-minute bins throughout a month, and then computes the 95 th percentile of these values as the billing volume. The 95 th percentile method has three attractive properties: it is simple to implement; it uses data that the provider typically already collects; and it approximates the load a customer imposes on the provider's network while forgiving a few anomalous traffic bursts.…”

Section: Introductionmentioning

confidence: 99%

Fair, Flexible and Feasible ISP Billing

Raja

Shakkottai

Dhamdhere

et al. 2014

SIGMETRICS Perform. Eval. Rev.

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The 95 th percentile method for calculating a customer's billable transit volume has been the industry standard used by transit providers for over a decade due to its simplicity. We recently showed [1] that 95 th percentile billing can be unfair, in that it does not reflect a customer's contribution to the provider's peak load. The 95 th percentile method is also inflexible, as it does not allow a provider to offer incentives to customers that contribute minimally to the provider's peak load. In this paper we propose a new transit billing optimization framework that is fair, flexible and computationally inexpensive. Our approach is based on the Provision Ratio, a metric that estimates the contribution of a customer to the provider's peak traffic. The proposed mechanism has fairness properties similar to the optimal (in terms of fairness) Shapley value allocation, with a much smaller computational complexity.

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On the 95-Percentile Billing Method

Cited by 56 publications

References 1 publication

Volume-Based Transit Pricing: Is 95 the Right Percentile?

Volume-Based Transit Pricing: Is 95 the Right Percentile?

Economic incentives for adopting congestion accountability protocols

Fair, Flexible and Feasible ISP Billing

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