Congestion avoidance and control
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State Transition Analysis: A Rule-Based Intrusion Detection Approach
IEEE Transactions on Software Engineering
The nature of statistical learning theory
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Analyzing stability in wide-area network performance
SIGMETRICS '97 Proceedings of the 1997 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
End-to-end Internet packet dynamics
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
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ACM SIGCOMM Computer Communication Review
Modeling TCP throughput: a simple model and its empirical validation
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Measurements and analysis of end-to-end Internet dynamics
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Making large-scale support vector machine learning practical
Advances in kernel methods
Critical path analysis of TCP transactions
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
A stochastic model of TCP/IP with stationary random losses
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
On the constancy of internet path properties
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
On the characteristics and origins of internet flow rates
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Predicting the Performance of Wide Area Data Transfers
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Multivariate resource performance forecasting in the network weather service
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
End-to-end available bandwidth: measurement methodology, dynamics, and relation with TCP throughput
IEEE/ACM Transactions on Networking (TON)
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Characterizing and Predicting TCP Throughput on the Wide Area Network
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
On the predictability of large transfer TCP throughput
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Improving accuracy in end-to-end packet loss measurement
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
A Proposed Framework for Calibration of Available Bandwidth Estimation Tools
ISCC '06 Proceedings of the 11th IEEE Symposium on Computers and Communications
SVM learning of IP address structure for latency prediction
Proceedings of the 2006 SIGCOMM workshop on Mining network data
Predicting short-transfer latency from TCP arcana: a trace-based validation
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Comparison of public end-to-end bandwidth estimation tools on high-speed links
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
PMSW: a passive monitoring system in wireless sensor networks
International Journal of Network Management
Text Semantic Mining Model Based on the Algebra of Human Concept Learning
International Journal of Cognitive Informatics and Natural Intelligence
Short-Term spatio-temporal forecasts of web performance by means of turning bands method
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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TCP throughput prediction is an important capability for networks where multiple paths exist between data senders and receivers. In this paper, we describe a new lightweight method for TCP throughput prediction. Our predictor uses Support Vector Regression (SVR); prediction is based on both prior file transfer history and measurements of simple path properties. We evaluate our predictor in a laboratory setting where ground truth can be measured with perfect accuracy. We report the performance of our predictor for oracular and practical measurements of path properties over a wide range of traffic conditions and transfer sizes. For bulk transfers in heavy traffic using oracular measurements, TCP throughput is predicted within 10% of the actual value 87% of the time, representing nearly a threefold improvement in accuracy over prior history-based methods. For practical measurements of path properties, predictions can be made within 10% of the actual value nearly 50% of the time, approximately a 60% improvement over history-based methods, and with much lower measurement traffic overhead. We implement our predictor in a tool called Path-Perf, test it in the wide area, and show that PathPerf predicts TCP throughput accurately over diverse wide area paths.