A machine learning approach to TCP throughput prediction
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An active measurement system for shared environments
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
On the accuracy of TCP throughput prediction for opportunistic wireless networks
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
A new form of DOS attack in a cloud and its avoidance mechanism
Proceedings of the 2010 ACM workshop on Cloud computing security workshop
A machine learning approach to TCP throughput prediction
IEEE/ACM Transactions on Networking (TON)
A case study of the accuracy of SNMP measurements
Journal of Electrical and Computer Engineering
End-to-end available bandwidth estimation tools, an experimental comparison
TMA'10 Proceedings of the Second international conference on Traffic Monitoring and Analysis
Unified architecture for network measurement: The case of available bandwidth
Journal of Network and Computer Applications
Estimation of the available bandwidth ratio of a remote link or path segments
Computer Networks: The International Journal of Computer and Telecommunications Networking
Active techniques for available bandwidth estimation: comparison and application
DataTraffic Monitoring and Analysis
A taxonomy of applying filter techniques to improve the available bandwidth estimations
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
Computer Networks: The International Journal of Computer and Telecommunications Networking
Federation Lifecycle Management Incorporating Coordination of Bio-inspired Self-management Processes
Journal of Network and Systems Management
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Examining the validity or accuracy of proposed available bandwidth estimation tools remains a challenging problem. A common approach consists of evaluating a newly developed tool using a combination of simple nstype simulations and feasible experiments in situ (i.e., using parts of the actual Internet). In this paper, we argue that this strategy tends to fall short of establishing a reliable "ground truth," and we advocate an alternative in vitro-like methodology for calibrating available bandwidth estimation tools that has not been widely used in this context. Our approach relies on performing controlled laboratory experiments and using tools to visualize and analyze the relevant tool-specific traffic dynamics. We present a case study of how two canonical available bandwidth estimation tools, SPRUCE and PATHLOAD, respond to increasingly more complex cross traffic and network path conditions. We expose measurement bias and algorithmic omissions that lead to poor tool calibration. As a result of this evaluation, we designed a calibrated available bandwidth estimation tool called YAZ that builds on the insights of PATHLOAD. We show that in head to head comparisons with SPRUCE and PATHLOAD, YAZ is significantly and consistently more accurate with respect to ground truth, and reports results more quickly with a small number of probes.