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
Measuring ISP topologies with rocketfuel
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
On the number of distributed measurement points for network tomography
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Simple network performance tomography
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
On the Cost-Quality Tradeoff in Topology-Aware Overlay Path Probing
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
An algebraic approach to practical and scalable overlay network monitoring
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Towards a scalable, adaptive and network-aware content distribution network
Towards a scalable, adaptive and network-aware content distribution network
Proceedings of the 2012 ACM conference on Internet measurement conference
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Monitoring systems that can detect path outages and periods of degraded performance are important for many distributed applications. Trivial pair-wise probing systems do not scale well and cannot be employed in large networks. To build scalable path monitoring systems, two different approaches have been proposed in the literature. The first approach [1], which we call the continuous or analogue model, takes real measurement values and infers the performance metrics of unmeasured paths using traditional (+,×) algebra. The second approach [2], which we call the Boolean model, takes binary values from measurements (e.g., whether the delay/loss of an end-to-end path is above a given threshold) and infers the performance quality of unmeasured paths using Boolean algebra. Both approaches exploit the fact that end-to-end paths share network links and hence that the measurements of some paths can be used to infer the performance on others. In this work, we are only interested in detecting whether the performance of a path is below an acceptable level or not. We show that when the number of beacons (nodes that can send probes and collect monitoring information) is small, the Boolean model requires fewer direct measurements; whereas for a large number of beacons the continuous model requires fewer direct measurements. When the number of beacons is significantly large, however, there is no difference in terms of the number of paths that we need to measure directly in both models. We verify the results by simulations on inferred network topologies and on real measurement data.