Probability, random processes, and estimation theory for engineers
Probability, random processes, and estimation theory for engineers
Deriving traffic demands for operational IP networks: methodology and experience
IEEE/ACM Transactions on Networking (TON)
Traffic matrix estimation: existing techniques and new directions
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An information-theoretic approach to traffic matrix estimation
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Structural analysis of network traffic flows
Proceedings of the joint international conference on Measurement and modeling of computer systems
A distributed approach to measure IP traffic matrices
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
A methodology for estimating interdomain web traffic demand
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Data streaming algorithms for accurate and efficient measurement of traffic and flow matrices
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Traffic matrices: balancing measurements, inference and modeling
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
The problem of synthetically generating IP traffic matrices: initial recommendations
ACM SIGCOMM Computer Communication Review
Providing public intradomain traffic matrices to the research community
ACM SIGCOMM Computer Communication Review
Traffic matrix tracking using Kalman filters
ACM SIGMETRICS Performance Evaluation Review - Special issue on the First ACM SIGMETRICS Workshop on Large Scale Network Inference (LSNI 2005)
Robust traffic matrix estimation with imperfect information: making use of multiple data sources
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Bibliography on cyclostationarity
Signal Processing
A fast lightweight approach to origin-destination IP traffic estimation using partial measurements
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
An independent-connection model for traffic matrices
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Estimating dynamic traffic matrices by using viable routing changes
IEEE/ACM Transactions on Networking (TON)
A data streaming algorithm for estimating entropies of od flows
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Reformulating the monitor placement problem: optimal network-wide sampling
CoNEXT '06 Proceedings of the 2006 ACM CoNEXT conference
Optimal sampling in state space models with applications to network monitoring
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Traffic monitor deployment in IP networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
An approximation method of origin-destination flow traffic from link load counts
Computers and Electrical Engineering
Effects of spatial aggregation on the characteristics of origin-destination pair traffic in funet
NEW2AN'07 Proceedings of the 7th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking
A toolchain for simplifying network simulation setup
Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques
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In this paper we investigate a new idea for traffic matrix estimation that makes the basic problem less under-constrained, by deliberately changing the routing to obtain additional measurements. Because all these measurements are collected over disparate time intervals, we need to establish models for each Origin-Destination (OD) pair to capture the complex behaviours of internet traffic. We model each OD pair with two components: the diurnal pattern and the fluctuation process. We provide models that incorporate the two components above, to estimate both the first and second order moments of traffic matrices. We do this for both stationary and cyclo-stationary traffic scenarios. We formalize the problem of estimating the second order moment in a way that is completely independent from the first order moment. Moreover, we can estimate the second order moment without needing any routing changes (i.e., without explicit changes to IGP link weights). We prove for the first time, that such a result holds for any realistic topology under the assumption of minimum cost routing and strictly positive link weights. We highlight how the second order moment helps the identification of the top largest OD flows carrying the most significant fraction of network traffic. We then propose a refined methodology consisting of using our variance estimator (without routing changes) to identify the top largest flows, and estimate only these flows. The benefit of this method is that it dramatically reduces the number of routing changes needed. We validate the effectiveness of our methodology and the intuitions behind it by using real aggregated sampled netflow data collected from a commercial Tier-1 backbone.