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Unifying split WAN architecture for cloud providers, addressing operational complexity and cost inefficiency. Introduces ONEWAN, a software-defined solution for Internet and inter-datacenter traffic, featuring innovative routing and traffic engineering t…
Optimizing network measurement tasks on programmable switches using Sketchovsky, a framework for efficient cross-sketch optimization and composition to reduce hardware resource usage.
Automated framework for optimizing cluster manager parameters in large-scale cloud environments, improving throughput and performance through reinforcement learning algorithms.
Scalable RDMA NIC architecture improving connection and network scalability while maintaining high performance and low CPU overhead, outperforming commercial RNICs in large-scale data centers.
Innovative congestion control system for ultra-fast data center networks, reducing latency and improving flow completion time while maintaining high utilization at speeds up to 400Gbps.
Explores IO-TCP, a split TCP stack design offloading disk I/O and packet transfer to SmartNIC, enhancing online content delivery performance by reducing CPU burden and improving scalability.
Explores a novel approach to datacenter server orchestration by offloading tasks to NICs, improving scalability, efficiency, latency, and throughput compared to software-only solutions.
Innovative system for improving short video streaming quality by predicting user swipe patterns and pre-buffering content, outperforming TikTok while reducing wasted data downloads.
Innovative video analytics framework integrating model reuse and online retraining for efficient, adaptive DNN models. Optimizes GPU allocation and leverages shared model zoo for improved performance across diverse vision tasks.
Explore futuristic integrated space-terrestrial networks with StarryNet, a framework enabling realistic and flexible experiments to evaluate global satellite dynamics and network behaviors.
Intercloud broker enabling seamless workload migration between clouds, creating a unified Sky Computing ecosystem for enhanced data compliance and protection against outages.
Proposes a simplified cloud network interface that reduces tenant complexity by 80-90%, shifting network management responsibilities to cloud providers while maintaining scalability and security.
Explores tradeoffs between energy consumption and performance in DNN training, proposing Zeus framework to optimize configurations for improved energy efficiency without compromising performance.
Innovative system for cost-effective training of large DNNs using preemptible instances, introducing redundant computations to enhance resilience and efficiency in distributed learning environments.
Innovative graph pattern mining system combining decomposition theory and edge sampling for efficient processing of massive graphs, outperforming existing solutions by orders of magnitude.
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