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
A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
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
Traffic engineering with estimated traffic matrices
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Structural analysis of network traffic flows
Proceedings of the joint international conference on Measurement and modeling of computer systems
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Modeling distances in large-scale networks by matrix factorization
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Traffic matrices: balancing measurements, inference and modeling
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A first step toward understanding inter-domain routing dynamics
Proceedings of the 2005 ACM SIGCOMM workshop on Mining network data
Simplifying the synthesis of internet traffic matrices
ACM SIGCOMM Computer Communication Review
IEEE/ACM Transactions on Networking (TON)
Providing public intradomain traffic matrices to the research community
ACM SIGCOMM Computer Communication Review
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
An independent-connection model for traffic matrices
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Sensitivity of PCA for traffic anomaly detection
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
IEEE Transactions on Information Theory
Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
IEEE Transactions on Information Theory
ASTUTE: detecting a different class of traffic anomalies
Proceedings of the ACM SIGCOMM 2010 conference
Detecting the performance impact of upgrades in large operational networks
Proceedings of the ACM SIGCOMM 2010 conference
Exploiting temporal stability and low-rank structure for localization in mobile networks
Proceedings of the sixteenth annual international conference on Mobile computing and networking
BasisDetect: a model-based network event detection framework
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Proceedings of the 6th International COnference
OLIC: online information compression for scalable hosting infrastructure monitoring
Proceedings of the Nineteenth International Workshop on Quality of Service
Joint time-frequency sparse estimation of large-scale network traffic
Computer Networks: The International Journal of Computer and Telecommunications Networking
Estimation of missing RTTs in computer networks: Matrix completion vs compressed sensing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Rapid detection of maintenance induced changes in service performance
Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
Clustered embedding of massive social networks
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Towards a statistical characterization of the interdomain traffic matrix
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part II
Inferring visibility: who's (not) talking to whom?
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Anatomy of a large european IXP
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Spatio-temporal compressive sensing and internet traffic matrices
IEEE/ACM Transactions on Networking (TON)
Evaluating compressive sampling strategies for performance monitoring of data centers
Proceedings of the 9th international conference on Autonomic computing
Inferring visibility: who's (not) talking to whom?
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
Anatomy of a large european IXP
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
On traffic matrix completion in the internet
Proceedings of the 2012 ACM conference on Internet measurement conference
A power laws-based reconstruction approach to end-to-end network traffic
Journal of Network and Computer Applications
A compressive sensing-based reconstruction approach to network traffic
Computers and Electrical Engineering
QoSPlan: A Measurement Based Quality of Service aware Network Planning Framework
Journal of Network and Systems Management
Robust assessment of changes in cellular networks
Proceedings of the ninth ACM conference on Emerging networking experiments and technologies
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Many basic network engineering tasks (e.g., traffic engineering, capacity planning, anomaly detection) rely heavily on the availability and accuracy of traffic matrices. However, in practice it is challenging to reliably measure traffic matrices. Missing values are common. This observation brings us into the realm of compressive sensing, a generic technique for dealing with missing values that exploits the presence of structure and redundancy in many real-world systems. Despite much recent progress made in compressive sensing, existing compressive-sensing solutions often perform poorly for traffic matrix interpolation, because real traffic matrices rarely satisfy the technical conditions required for these solutions. To address this problem, we develop a novel spatio-temporal compressive sensing framework with two key components: (i) a new technique called Sparsity Regularized Matrix Factorization (SRMF) that leverages the sparse or low-rank nature of real-world traffic matrices and their spatio-temporal properties, and (ii) a mechanism for combining low-rank approximations with local interpolation procedures. We illustrate our new framework and demonstrate its superior performance in problems involving interpolation with real traffic matrices where we can successfully replace up to 98% of the values. Evaluation in applications such as network tomography, traffic prediction, and anomaly detection confirms the flexibility and effectiveness of our approach.