AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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BackTrend is introduced, a retrospective benchmark in which, given a mature target topic and a temporal evidence constraint, systems must recover two types of precursors: problem-space signals, underrecognized research problems, and solution-space signals, emerging methods for known problems.
DeepShare is a scheduler that uses a continuous tenant-assurance signal to coordinate these decisions at runtime to achieve a more advantageous utilization-QoS trade-off than optimizing quotas, scheduling, and resource sharing independently.
A prediction-guided runtime that uses workflow forecasts to construct and optimize a physical execution graph and reduces end-to-end makespan and overall p95 completion latency under burst arrivals by up to 36.8% and 25.8% over state-of-the-art workflow schedulers.
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