Sourya Saha
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This paper investigates a network side-channel vulnerability in multi-tenant datacenter fabrics caused by shared congestion behavior, achieving up to 97.3% run-level accuracy in workload inference.
Proposed ProFlow, a proactive flow-placement framework using distributed telemetry signals and offline-trained RL for identifying precursor congestion conditions and rerouting protected flows in multi-tenant datacenter networks, achieving approximately 40% higher mean throughput and initiating rerouting decisions around 34 seconds earlier on average.
Papers
Round Trip Time: A Benign Signal or an Indirect Window into Datacenter Workloads?
This paper investigates a network side-channel vulnerability in multi-tenant datacenter fabrics caused by shared congestion behavior, achieving up to 97.3% run-level accuracy in workload inference.