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Enhancing Flexibility for Dynamic Time-Sensitive Network Configurations

FA2: Fast, Accurate Autoscaling for Serving Deep Learning Inference with SLA Guarantees

GreenTCAM: Energy Efficient Memristor-Based TCAM for Match-Action Processing

Network Testing Utilizing Programmable Network Hardware

On Memristors for Enabling Energy Efficient and Enhanced Cognitive Network Functions

On the Incremental Reconfiguration of Time-sensitive Networks at Runtime

PANDA: Performance prediction for parallel and dynamic stream processing

Towards adaptive quality-aware Complex Event Processing in the Internet of Things

Towards Energy Efficient Memristor-based TCAM for Match-Action Processing

Travel light: State shedding for efficient operator migration

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