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GITBOOK-208: Upload the paper list of HotNets'24
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| # HotNets 2024 | ||
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| ## Meta Info | ||
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| Homepage: [https://conferences.sigcomm.org/hotnets/2024/index.html](https://conferences.sigcomm.org/hotnets/2024/index.html) | ||
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| Paper list: [https://conferences.sigcomm.org/hotnets/2024/program.html](https://conferences.sigcomm.org/hotnets/2024/program.html) | ||
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| ## Papers | ||
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| ### Large Language Models (LLMs) | ||
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| * Networking for LLM Training | ||
| * I’ve Got 99 Problems But FLOPS Ain’t One \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-333.pdf)] | ||
| * University Politehnica of Bucharest | ||
| * The future of large-scale AI infrastructure requires | ||
| * (1) novel wide-area transports for inter-DC communication; | ||
| * (2) a multipath transport and novel datacenter topologies for intra-datacenter communication; | ||
| * (3) high-speed scale-up networks and transport. | ||
| * LLM for Networking | ||
| * Designing Network Algorithms via Large Language Models \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-88.pdf)] | ||
| * MSR | ||
| * **NADA**: Network Algorithm Design Automation via LLMs | ||
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| ### Congestion Control | ||
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| * MLTCP: A Distributed Technique to Approximate Centralized Flow Scheduling For Machine Learning \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-166.pdf)] | ||
| * MIT | ||
| * Scale the congestion window size (or sending rate) based on the number of bytes sent at each iteration. | ||
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| ### Trading Systems | ||
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| * Network Design Considerations for Trading Systems \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-262.pdf)] | ||
| * Jane Street | ||
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| ### Caching | ||
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| * Revisiting Cache Freshness for Emerging Real-Time Applications \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-21.pdf)] | ||
| * UC Berkeley | ||
| * At real-time timescales, making freshness decisions in response to incoming writes is more efficient than TTL-based policies. | ||
| * Rethinking Web Caching: An Optimization for the Latency-Constrained Internet \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-124.pdf)] | ||
| * Shahid Beheshti University & Università della Svizzera italiana & Institute for Research in Fundamental Sciences & Sharif University of Technology | ||
| * Web servers _proactively_ provide clients with the latest validation tokens for resources during the initial step of page loading → Allow browsers to use unchanged cached content without unnecessary round trips. | ||
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| ### Performance Analysis | ||
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| * End-to-End Performance Analysis of Learning-enabled Systems \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-138.pdf)] | ||
| * USC & Hebrew University of Jerusalem & Rice University & Microsoft | ||
| * A gray-box approach (leverage partial information) → Use gradient to analyze the performance of DNNs. | ||
| * Buffy: A Formal Language-Based Framework for Network Performance Analysis \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-2.pdf)] | ||
| * UWaterloo & Princeton | ||
| * Language abstractions to enable users to model network functionality and analysis tasks in an imperative solver-agnostic program. | ||
| * A framework to transform them into a representation that can be analyzed by the appropriate solver. | ||
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| ### Reliability | ||
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| * Automatic Configuration Repair \[[Paper](https://conferences.sigcomm.org/hotnets/2024/papers/hotnets24-398.pdf)] | ||
| * XJTU & ByteDance | ||
| * Draw some insights from the field of Automatic Software Repair (ASR). | ||
| * Propose **localize-fix-validate** as a possible approach to realize **Automatic Configuration Repair (ACR)**. | ||
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| ## Acronyms | ||
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| * TTL: Time-To-Live | ||
| * DNN: Deep Neural Networks | ||
| * DC: Datacenter |