The Fourier-series method for inverting transforms of probability distributions
Queueing Systems: Theory and Applications - Numerical computations in queues
Properties and prediction of flow statistics from sampled packet streams
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice
ACM Transactions on Computer Systems (TOCS)
Estimating flow distributions from sampled flow statistics
IEEE/ACM Transactions on Networking (TON)
Why flow-completion time is the right metric for congestion control
ACM SIGCOMM Computer Communication Review
IEEE/ACM Transactions on Networking (TON)
Fisher information of sampled packets: an application to flow size estimation
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
A Unified Framework for Numerically Inverting Laplace Transforms
INFORMS Journal on Computing
Maximum likelihood estimation of the flow size distribution tail index from sampled packet data
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
On the characteristics and reasons of long-lived internet flows
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Some observations of internet stream lifetimes
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
Cluster processes: a natural language for network traffic
IEEE Transactions on Signal Processing
Understanding Internet traffic streams: dragonflies and tortoises
IEEE Communications Magazine
Fisher Information in Flow Size Distribution Estimation
IEEE Transactions on Information Theory
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The flow duration distribution is an important metric to the network operator for traffic prediction and accounting but also arguably from the viewpoint of the user. The inversion problem of recovering the flow duration distribution from sampled traffic is addressed here under several sampling methods. A theoretical framework for the inversion problem is developed using a probabilistic flow model. In this framework, direct equations for the distributions of sampled flow quantities are derived based on the distributions of original flow characteristics. The inversion of these equations provides estimators for the flow duration distribution. Finally, the inversion techniques under several sampling schemes are evaluated on two Internet traces.