Wide-area traffic: the failure of Poisson modeling
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Self-similarity in World Wide Web traffic: evidence and possible causes
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
The changing nature of network traffic: scaling phenomena
ACM SIGCOMM Computer Communication Review
Dynamics of IP traffic: a study of the role of variability and the impact of control
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Templates for the solution of algebraic eigenvalue problems: a practical guide
Templates for the solution of algebraic eigenvalue problems: a practical guide
Characteristics of network traffic flow anomalies
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Wide-area Internet traffic patterns and characteristics
IEEE Network: The Magazine of Global Internetworking
Monitoring the Macroscopic Effect of DDoS Flooding Attacks
IEEE Transactions on Dependable and Secure Computing
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Analyzing spatial-temporal characteristics of traffic in large-scale networks requires both a suitable analysis method and a means to reduce the amount of data that must be collected. Of particular interest would be techniques that reduce the amount of data needed, while simultaneously retaining the ability to monitor spatial-temporal behavior network-wide. In this paper, we propose such a method, motivated by insights about network dynamics at the macroscopic level. We define a weight vector to build up information about the influence of local behavior over the whole network. By taking advantage of increased correlations arising in large networks, this method might require only a few observation points to capture shifting network-wide patterns over time. This paper explains the principles underlying our proposed method, and describes the associated analytical process.