Information about the topology and link-level characteristics of a network is critical for many applications including network diagnostics and management. However, this information is not always directly accessible; subnetworks may not cooperate in releasing information and widespread local measurement can be prohibitively expensive. Network tomographic techniques obviate the need for network cooperation, but the majority assume probing from a single source, which imposes scalability limitations because sampling traffic is concentrated on network links close to the source. We describe a multiple source, end-toend sampling architecture that uses coordinated transmission of carefully engineered multi-packet probes to jointly infer logical topology and estimate link-level performance characteristics. We commence by demonstrating that the general multiple source, multiple destination tomography problem can be formally reduced to the two source, two destination case, allowing the immediate generalization of any sampling techniques developed for the simpler, smaller scenario. We then describe a method for testing whether links are shared in the topologies perceived by
individual sources, and describe how to fuse the measurements in the shared case to generate more accurate estimates of the link-level performance statistics.
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