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Innovative framework for optimizing network-wide monitoring in diverse, dynamic environments. Reduces resource overhead while maintaining performance, coverage, and accuracy through automated profiling and task allocation.
Automated technique for verifying network function binaries without source code, using ghost maps to model data structures and infer control flow, enabling operators to ensure reliability of proprietary software.
Explores Swift, an adaptive video streaming system using layered neural codecs for fine-grained rate adaptation, offering improved compression and decoding efficiency over traditional layered coding approaches.
Innovative task sampling approach for cluster job scheduling, improving runtime property estimation and reducing job completion time compared to history-based predictors.
Accelerates container provisioning for edge and WAN environments by redesigning deployment protocols, filesystem, and image storage, achieving 3x faster deployment with minimal overhead.
Explore privacy-preserving video analytics with Privid, a system enforcing duration-based privacy for public surveillance footage while maintaining utility for various applications.
Innovative clock synchronization system leveraging local clock properties to improve accuracy and failure tolerance, reducing drift by up to 2000× for high-performance applications requiring sub-microsecond precision.
Explore neural-enhanced volumetric video streaming with YuZu, boosting quality and efficiency through 3D super resolution, QoE modeling, and adaptive resource management for immersive 6DoF experiences.
High-bandwidth anonymous file broadcasting system optimizing for few broadcasters and many subscribers. Offers improved throughput, malicious client prevention, and broadcaster deanonymization protection.
Explores performance interfaces for network functions, introducing PIX tool to extract and analyze performance data, aiding developers and operators in optimizing network systems.
Explore DONAR, a system enabling anonymous VoIP over Tor with high quality-of-experience through innovative traffic management and performance optimization techniques.
Automated system for converting uncompilable P4 programs into compilable versions, addressing fitting issues in programmable switches and significantly reducing development time.
Explores efficient scheduling policies for microsecond-scale tasks in datacenters, comparing load-balancing and core allocation strategies to optimize latency and resource utilization.
Continuous learning for edge video analytics models, addressing data drift and balancing inference-retraining tradeoffs. Ekya optimizes resource allocation for improved accuracy with fewer GPU resources.
Decentralized WAN traffic engineering system slicing networks into fault domains, maximizing throughput without central coordination while reducing traffic loss from controller failures.
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