Application of sampling methodologies to network traffic characterization
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Digital signal processing (3rd ed.): principles, algorithms, and applications
Digital signal processing (3rd ed.): principles, algorithms, and applications
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
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Identifying elephant flows through periodically sampled packets
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Ranking flows from sampled traffic
CoNEXT '05 Proceedings of the 2005 ACM conference on Emerging network experiment and technology
IEEE/ACM Transactions on Networking (TON)
Impact of packet sampling on anomaly detection metrics
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Trajectory sampling with unreliable reporting
IEEE/ACM Transactions on Networking (TON)
Fast, memory efficient flow rate estimation using runs
IEEE/ACM Transactions on Networking (TON)
Spectral probing, crosstalk and frequency multiplexing in internet paths
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Network anomaly detection and classification via opportunistic sampling
IEEE Network: The Magazine of Global Internetworking - Special issue title on recent developments in network intrusion detection
Learn more, sample less: control of volume and variance in network measurement
IEEE Transactions on Information Theory
A frequency domain model to predict the estimation accuracy of packet sampling
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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Packet sampling techniques introduce measurement errors that should be carefully handled in order to correctly characterize the network behavior. In the literature several works have studied the statistical properties of packet sampling and the way it should be inverted to recover the original network measurements. Here we take the new direction of studying the spectral properties of packet sampled traffic. A novel technique to model the impact of packet sampling is proposed based on a theoretical analysis of network traffic in the frequency domain. Moreover, a real-time algorithm is also presented to detect the spectrum portion of the network traffic that can be restored once packet sampling has been applied. Preliminary experimental results are reported to validate the proposed approach.