On the self-similar nature of Ethernet traffic
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Wide-area traffic: the failure of Poisson modeling
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
On economic heavy hitters: shapley value analysis of 95th-percentile pricing
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
A case study of the accuracy of SNMP measurements
Journal of Electrical and Computer Engineering
On blind mice and the elephant: understanding the network impact of a large distributed system
Proceedings of the ACM SIGCOMM 2011 conference
CIPT: using tuangou to reduce IP transit costs
Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
On the dynamics of locators in LISP
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part I
IXP traffic: a macroscopic view
Proceedings of the 7th Latin American Networking Conference
Sharing the cost of backbone networks: cui bono?
Proceedings of the 2012 ACM conference on Internet measurement conference
Large-scale measurement and characterization of cellular machine-to-machine traffic
IEEE/ACM Transactions on Networking (TON)
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The 95-percentile method is used widely for billing ISPs and websites. In this work, we characterize important aspects of the 95-percentile method using a large set of traffic traces. We first study how the 95-percentile depends on the aggregation window size. We observe that the computed value often follows a noisy decreasing trend along a convex curve as the window size increases. We provide theoretical justification for this dependence using the self-similar model for Internet traffic and discuss observed more complex dependencies in which the 95-percentile increases with the window size. Secondly, we quantify how variations on the window size affect the computed 95-percentile. In our experiments, we find that reasonable differences in the window size can account for an increase between 4.1% and 42.5% in the monthly bill of medium and low-volume sites. In contrast, for sites with average traffic rates above 10Mbps the fluctuation of the 95-percentile is bellow 2.9%. Next, we focus on the use of flow data in hosting environments for billing individual sites. We describe the byte-shifting effect introduced by flow aggregation and quantify how it can affect the computed 95-percentile. We find that in our traces it can both decrease and increase the computed 95-percentile with the largest change being a decrease of 9.3%.