In the context of network traffic analysis, we address the problem of estimating the tail index of flow (or more gener-ally of any group) size distribution from the observation of a sampled population of packets (individuals). We give an exhaustive bibliography of the existing methods and show the relations between them. The main contribution of this work is then to propose a new method to estimate the tail index from sampled data, based on the resolution of the maximum likelihood problem. To assess the performance of our method, we present a full performance evaluation based on numerical simulations, and also on a real traffic trace corresponding to internet traffic recently acquired
In the Internet, a statistical perspective of global traffic flows has been considered as an importa...
With the emergence of computer networks as one of the primary modes of communication, and with thei...
Estimation of flow volumes in computer networks involves the use of data that are either highly aggr...
International audienceIn the context of network traffic analysis, we address the problem of estimati...
Statistical information about the flow sizes in the traffic passing through a network link helps a n...
Abstract—We show in this note that by deterministic packet sampling, the tail of the distribution of...
Knowing the distribution of the sizes of traffic flows passing through a network link helps a networ...
In this paper, we revisit the estimation of the size distribution of packet flows in Internet traffi...
Packet sampling is widely used in network monitoring. Sam-pled packet streams are often used to dete...
Understanding the characteristics of traffic flows is crucial for allocating the necessary resources...
Many researchers have discussed the effects of heavy-tailedness in network traffic patterns and show...
We show in this note that by deterministic packet sampling, the tail of the distribution of the orig...
The flow size distribution is a useful metric for traffic modeling and management. It is well known ...
The flow size distribution is a useful metric for traffic modeling and management. Its estimation ba...
International audienceIn this paper, we study the impact of the flow-size distribution on network pe...
In the Internet, a statistical perspective of global traffic flows has been considered as an importa...
With the emergence of computer networks as one of the primary modes of communication, and with thei...
Estimation of flow volumes in computer networks involves the use of data that are either highly aggr...
International audienceIn the context of network traffic analysis, we address the problem of estimati...
Statistical information about the flow sizes in the traffic passing through a network link helps a n...
Abstract—We show in this note that by deterministic packet sampling, the tail of the distribution of...
Knowing the distribution of the sizes of traffic flows passing through a network link helps a networ...
In this paper, we revisit the estimation of the size distribution of packet flows in Internet traffi...
Packet sampling is widely used in network monitoring. Sam-pled packet streams are often used to dete...
Understanding the characteristics of traffic flows is crucial for allocating the necessary resources...
Many researchers have discussed the effects of heavy-tailedness in network traffic patterns and show...
We show in this note that by deterministic packet sampling, the tail of the distribution of the orig...
The flow size distribution is a useful metric for traffic modeling and management. It is well known ...
The flow size distribution is a useful metric for traffic modeling and management. Its estimation ba...
International audienceIn this paper, we study the impact of the flow-size distribution on network pe...
In the Internet, a statistical perspective of global traffic flows has been considered as an importa...
With the emergence of computer networks as one of the primary modes of communication, and with thei...
Estimation of flow volumes in computer networks involves the use of data that are either highly aggr...