Efficient and portable combined random number generators
Communications of the ACM
Practical performance of Bloom filters and parallel free-text searching
Communications of the ACM
Application of sampling methodologies to network traffic characterization
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Trajectory sampling for direct traffic observation
IEEE/ACM Transactions on Networking (TON)
Estimating flow distributions from sampled flow statistics
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Packet Trains--Measurements and a New Model for Computer Network Traffic
IEEE Journal on Selected Areas in Communications
A parameterizable methodology for Internet traffic flow profiling
IEEE Journal on Selected Areas in Communications
Measurement data reduction through variation rate metering
INFOCOM'10 Proceedings of the 29th conference on Information communications
Efficient packet sampling for accurate traffic measurements
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Traffic measurement and monitoring are an important component of network QoS management and traffic engineering. With high speed Internet links, efficient and effective packet sampling techniques for traffic measurement are not only desirable, but increasingly becoming a necessity. Packet sampling has become an attractive and scalable means to measure flow data on high speed links. Passive traffic measurement increasingly employs sampling at the packet level and makes inferences from sampled network traffic. However, it meets difficulty in estimating the original flow distribution. To circumvent the problem, we propose and analyze a double sampling technique for flow measurement. In particular, we rewrite the expectation maximization (EM) algorithm that estimates flow distribution for double sampling. Using real network traffic traces, we show that the proposed double sampling technique indeed produces the desired accuracy in estimating the flow distribution.