Paper Digest: SIGCOMM 2025 Papers & Highlights

September 3, 2025September 5, 2025 admin

SIGCOMM is one of the top data communications and networking conferences in the world. To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper. Readers are encouraged to read these machine generated highlights to quickly get the main idea of each paper.

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To search for papers presented at SIGCOMM-2025 on a specific topic, please make use of the search by venue (SIGCOMM-2025) service. To summarize the latest research published at SIGCOMM-2025 on a specific topic, you can utilize the review by venue (SIGCOMM-2025) service. To synthesizes the findings from SIGCOMM 2025 into comprehensive reports, give a try to SIGCOMM-2025 Research. If you are interested in browsing papers by author, we have a comprehensive list of all SIGCOMM-2025 authors & their papers. Additionally, you may want to explore our “Best Paper” Digest (SIGCOMM), which lists the most influential SIGCOMM papers in the recent years.

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TABLE 1: Paper Digest: SIGCOMM 2025 Papers & Highlights

	Paper	Author(s)
1	InfiniteHBD: Building Datacenter-Scale High-Bandwidth Domain for LLM with Optical Circuit Switching Transceivers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Switch-GPU hybrid HBDs (e.g., TPUv4) take a middle-ground approach, but the fault explosion radius remains large.We propose InfiniteHBD, a transceiver-centric HBD architecture that integrates connectivity and dynamic switching at the transceiver level by embedding Optical Circuit Switching (OCS) within each transceiver.	Chenchen Shou; Guyue Liu; Hao Nie; Huaiyu Meng; Yu Zhou; Yimin Jiang; Wenqing Lv; Yelong Xu; Yuanwei Lu; Zhang Chen; Yanbo Yu; Yichen Shen; Yibo Zhu; Daxin Jiang;
2	DistTrain: Addressing Model and Data Heterogeneity with Disaggregated Training for Multimodal Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: DistTrain incorporates two novel disaggregation techniques to address model and data heterogeneity, respectively.	Zili Zhang; Yinmin Zhong; Yimin Jiang; Hanpeng Hu; Jianjian Sun; Zheng Ge; Yibo Zhu; Daxin Jiang; Xin Jin;
3	SCX: Stateless KV-Cache Encoding for Cloud-Scale Confidential Transformer Serving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work proposes stateless KV-cache encoding (SCX), a novel framework that encodes the intermediate key-value cache during Transformer inference using user-controlled keys.	Mu Yuan; Lan Zhang; Liekang Zeng; Siyang Jiang; Bufang Yang; Di Duan; Guoliang Xing;
4	ResCCL: Resource-Efficient Scheduling for Collective Communication Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes ResCCL, a novel CCL backend designed for Resource-Efficient Scheduling to address key limitations in current systems.	Tongrui Liu; Chenyang Hei; Fuliang Li; Chengxi Gao; Jiamin Cao; Tianshu Wang; Ennan Zhai; Xingwei Wang;
5	Albatross: A Containerized Cloud Gateway Platform with FPGA-accelerated Packet-level Load Balancing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: After evaluating multiple options, we developed Albatross, our 3rd gen cloud gateway based on FPGA and x86 CPUs.	Jianyuan Lu; Shunmin Zhu; Jun Liang; Yuxiang Lin; Tian Pan; Yisong Qiao; Yang Song; Wenqiang Su; Yixin Xie; Yanqiang Li; Enge Song; Shize Zhang; Xiaoqing Sun; Rong Wen; Xionglie Wei; Biao Lyu; Xing Li;
6	Revisiting RDMA Reliability for Lossy Fabrics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we revisit RDMA reliability with the goals of being independent of PFC, compatible with packet-level load balancing, free from RTO, and friendly to hardware offloading.	Wenxue Li; Xiangzhou Liu; Yunxuan Zhang; Zihao Wang; Wei Gu; Tao Qian; Gaoxiong Zeng; Shoushou Ren; Xinyang Huang; Zhenghang Ren; Bowen Liu; Junxue Zhang; Kai Chen; Bingyang Liu;
7	Software-based Live Migration for RDMA Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes MigrRDMA, a software-based RDMA live migration that does not rely on any extra hardware support.	Xiaoyu Li; Ran Shu; Yongqiang Xiong; Fengyuan Ren;
8	ByteDance Jakiro: Enabling RDMA and TCP Over Virtual Private Cloud Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce Jakiro, an innovative framework of vNIC design that supports both RDMA and TCP within ByteDance Cloud.	Yirui Liu; Lidong Jiang; Deguo Li; Daxiang Kang; Zhaoyang Wei; Yuqi Chai; Bin Niu; Ke Lin; Xiaoning Ding; Jianwen Pi; Hao Luo;
9	LeoCC: Making Internet Congestion Control Robust to LEO Satellite Dynamics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, LeoCC employs a suite of new techniques to: (i) efficiently detect reconfiguration on the endpoint; (ii) apply a reconfiguration-aware model to characterize and estimate network conditions accurately; and (iii) precisely regulate the sending rate.	Zeqi Lai; Zonglun Li; Qian Wu; Hewu Li; Jihao Li; Xin Xie; Yuanjie Li; Jun Liu; Jianping Wu;
10	Censys: A Map of Internet Hosts and Services Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Since then, as we have learned more about how best to capture the complex behavior of Internet services and begun to serve commercial and government users, we have re-architected every aspect of how Censys operates. Motivated by requests from the community,we present Censys’ evolution and current architecture, evaluate its visibility, and detail how Censys has been used by research, industry, and government.	Zakir Durumeric; Hudson Clark; Jeff Cody; Elliot Cubit; Matt Ellison; Liz Izhikevich; Ariana Mirian;
11	Edge Caching As Differentiation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the—in our opinion—surprising QoE disparities that result from edge caching and discuss their implications.	Muhammad Abdullah; Mughees Ur Rehman; Pavlos Nikolopoulos; Katerina Argyraki;
12	Raha: A General Tool to Analyze WAN Degradation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present extensive experiments on Microsoft’s production network and those of Topology Zoo that demonstrate Raha is scalable and can effectively solve the problem.	Behnaz Arzani; Sina Taheri; Pooria Namyar; Ryan Beckett; Siva Kesava Reddy Kakarla; Elnaz Jalilipour;
13	ParserHawk: Hardware-aware Parser Generator Using Program Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We leverage program-synthesis-based techniques to build a parser compiler, ParserHawk, for 2 network devices: the Intel Infrastructure Processing Unit (IPU) and the Barefoot Tofino programmable switch.	Xiangyu Gao; Jiaqi Gao; Karan Kumar G; Muhammad Haseeb; Ennan Zhai; Bili Dong; Joseph Tassarotti; Srinivas Narayana; Anirudh Sivaraman;
14	Nezha: SmartNIC-based Virtual Switch Load Sharing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Nezha, a distributed vSwitch load sharing system.	Xing Li; Enge Song; Bowen Yang; Tian Pan; Ye Yang; Qiang Fu; Yang Song; Yilong Lv; Zikang Chen; Jianyuan Lu; Shize Zhang; Xiaoqing Sun; Rong Wen; Xionglie Wei; Biao Lyu; Zhigang Zong; Qinming He; Shunmin Zhu;
15	Mosaic: Breaking The Optics Versus Copper Trade-off with A Wide-and-Slow Architecture and MicroLEDs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We demonstrate an end-to-end Mosaic prototype with 100 optical channels, each transmitting at 2 Gbps, and show how it scales to 800 Gbps and beyond with a reach of up to 50 m. Mosaic is protocol-agnostic and seamlessly integrates with existing network infrastructure, providing a practical and scalable solution for future networks.	Kaoutar Benyahya; Ariel Gomez Diaz; Junyi Liu; Vassily Lyutsarev; Marianna Pantouvaki; Kai Shi; Shawn Yohanes Siew; Hitesh Ballani; Thomas Burridge; Daniel Cletheroe; Thomas Karagiannis; Brian Robertson; Ant Rowstron; Mengyang Yang; Paolo Costa;
16	Falcon: A Reliable, Low Latency Hardware Transport Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Falcon, the first hardware transport that supports multiple Upper Layer Protocols (ULPs) and heterogeneous application workloads in general-purpose Ethernet datacenter environments (with losses and without special switch support).	Arjun Singhvi; Nandita Dukkipati; Prashant Chandra; Hassan M. G. Wassel; Naveen Kr. Sharma; Anthony Rebello; Henry Schuh; Praveen Kumar; Behnam Montazeri; Neelesh Bansod; Sarin Thomas; Inho Cho; Hyojeong Lee Seibert; Baijun Wu; Rui Yang; Yuliang Li; Kai Huang; Qianwen Yin; Abhishek Agarwal; Srinivas Vaduvatha; Weihuang Wang; Masoud Moshref; Tao Ji; David Wetherall; Amin Vahdat;
17	Hattrick: Solving Multi-Class TE Using Neural Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present Hattrick, the first ML-based approach for handling multiple traffic classes, a key requirement of cloud and ISP WANs.	Abd AlRhman AlQiam; Zhuocong Li; Satyajeet Singh Ahuja; Zhaodong Wang; Ying Zhang; Sanjay G. Rao; Bruno Ribeiro; Mohit Tawarmalani;
18	CClinguist: An Expert-Free Framework for Future-Compatible Congestion Control Algorithm Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Traditional CCA census tools, however, rely heavily on manual configuration and construction, necessitating significant human effort to keep pace with the introduction of new CCAs.In this paper, we introduce the CClinguist framework, which is an expert-free CCA identification tool.	Jiahui Li; Han Qi; Ruyi Yao; Jialin Wei; Ruoshi Sun; Zixuan Chen; Sen Liu; Yang Xu;
19	The Sweet Danger of Sugar: Debunking Representation Learning for Encrypted Traffic Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, with a networking expert mindset, we critically reassess their performance.	Yuqi Zhao; Giovanni Dettori; Matteo Boffa; Luca Vassio; Marco Mellia;
20	DeepSpace: Super Resolution Powered Efficient and Reliable Satellite Image Data Acquistion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose DeepSpace, a new deep learning-based super-resolution approach that compresses satellite imagery by over two orders of magnitude, while preserving image quality using a tailored mixture of experts (MoE) super-resolution framework.	Chuanhao Sun; Yu Zhang; Bill Tao; Deepak Vasisht; Mahesh Marina;
21	Agua: A Concept-Based Explainer for Learning-Enabled Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Agua, an explainability framework that explains a model’s decisions using high-level, human understandable concepts (e.g., volatile network conditions).	Sagar Patel; Dongsu Han; Nina Narodytska; Sangeetha Abdu Jyothi;
22	Intent-Driven Network Management with Multi-Agent LLMs: The Confucius Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present our experience developing Confucius, a multi-agent framework for network management at Meta.	Zhaodong Wang; Samuel Lin; Guanqing Yan; Soudeh Ghorbani; Minlan Yu; Jiawei Zhou; Nathan Hu; Lopa Baruah; Sam Peters; Srikanth Kamath; Jerry Yang; Ying Zhang;
23	Hermes: Enhancing Layer-7 Cloud Load Balancers with Userspace-Directed I/O Event Notification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Since each worker serves multi-tenant traffic, inter-worker load balancing is critical to avoid worker overload and preserve tenant performance isolation.In this work, we present Hermes, a userspace-directed I/O event notification framework to enhance L7 LBs.	Tian Pan; Enge Song; Yueshang Zuo; Shaokai Zhang; Yang Song; Jiangu Zhao; Wengang Hou; Jianyuan Lu; Xiaoqing Sun; Shize Zhang; Ye Yang; Jiao Zhang; Tao Huang; Biao Lyu; Xing Li; Rong Wen; Zhigang Zong; Shunmin Zhu;
24	CEIO: A Cache-Efficient Network I/O Architecture for NIC-CPU Data Paths Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents CEIO, a novel cache-efficient network I/O architecture that employs proactive rate control and elastic buffering to achieve zero LLC misses in the I/O data path while ensuring the effectiveness of DDIO and RDMA under various network conditions.	Bowen Liu; Xinyang Huang; Qijing Li; Zhuobin Huang; Yijun Sun; Wenxue Li; Junxue Zhang; Ping Yin; Kai Chen;
25	Centralium: A Hybrid Route-Planning Framework for Large-Scale Data Center Network Migrations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we highlight the unique challenges of production migration and illustrate how native BGP falls short, unable to encode both sequential and spatial conditions.	Yikai Lin; Mohab Gawish; Shih-Hao Tseng; Lixin Gao; Cen Zhao; John Tracey; Sunyi Shao; Hyojeong Kim; Ying Zhang;
26	ZENITH: Towards A Formally Verified Highly-Available Control Plane Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Zenith, a microservice-based controller that avoids inconsistencies by design rather than always relying on recovery mechanisms.	Pooria Namyar; Arvin Ghavidel; Mingyang Zhang; Harsha V. Madhyastha; Srivatsan Ravi; Chao Wang; Ramesh Govindan;
27	Firefly: Scalable, Ultra-Accurate Clock Synchronization for Datacenters Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Firefly, a software-driven datacenter clock sync system, scalably, cost-effectively, and reliably achieves very high clock sync accuracy. It employs a distributed consensus algorithm on a random overlay graph to rapidly converge to a common time while applying gradual adjustments to device hardware clocks.	Pooria Namyar; Yuliang Li; Weitao Wang; Nandita Dukkipati; Kk Yap; Junzhi Gong; Chen Chen; Peixuan Gao; Devdeep Ray; Gautam Kumar; Yidan Ma; Ramesh Govindan; Amin Vahdat;
28	Alibaba Stellar: A New Generation RDMA Network for Cloud AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These issues include lengthy container initialization times, hardware resource constraints, and inefficient traffic steering. To address these challenges, we propose Stellar, a new generation RDMA network for cloud AI.	Jie Lu; Jiaqi Gao; Fei Feng; Zhiqiang He; Menglei Zheng; Kun Liu; Jun He; Binbin Liao; Suwei Xu; Ke Sun; Yongjia Mo; Qinghua Peng; Jilie Luo; Qingxu Li; Gang Lu; Zishu Wang; Jianbo Dong; Kunling He; Sheng Cheng; Jiamin Cao; Hairong Jiao; Pengcheng Zhang; Shu Ma; Lingjun Zhu; Chao Shi; Yangming Zhang; Yiquan Chen; Wei Wang; Shuhong Zhu; Xingru Li; Qiang Wang; Jiang Liu; Chao Wang; Wei Lin; Ennan Zhai; Jiesheng Wu; Qiang Liu; Binzhang Fu; Dennis Cai;
29	DNSLogzip: A Novel Approach to Fast and High-Ratio Compression for DNS Logs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Built on in-depth empirical studies of real-world DNS log datasets, we identify four key inter-line and intra-line characteristics that enable effective reduction of redundancies without information loss.	Yunwei Dai; Guyue Liu; Tao Huang; Shuo Wang; Yong Wang; Xingli Wu; Lei Song; Heshun Li; Chuang Wang; Fanglong Hu; Hong Sun; Yanan Li;
30	Hawkeye: Diagnosing RDMA Network Performance Anomalies with PFC Provenance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Hawkeye, an accurate and efficient RDMA NPA diagnosis system based on PFC provenance.	Shicheng Wang; Menghao Zhang; Xiao Li; Qiyang Peng; Haoyuan Yu; Zhiliang Wang; Mingwei Xu; Xiaohe Hu; Jiahai Yang; Xingang Shi;
31	Towards LLM-Based Failure Localization in Production-Scale Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present BiAn, an LLM-based framework designed to assist operators in efficient incident investigation.	Chenxu Wang; Xumiao Zhang; Runwei Lu; Xianshang Lin; Xuan Zeng; Xinlei Zhang; Zhe An; Gongwei Wu; Jiaqi Gao; Chen Tian; Guihai Chen; Guyue Liu; Yuhong Liao; Tao Lin; Dennis Cai; Ennan Zhai;
32	SkyNet: Analyzing Alert Flooding from Severe Network Failures in Large Cloud Infrastructures Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents SkyNet, a network analysis system to extract scope and severity information from alert floods.	Bo Yang; Huanwu Hu; Yifan Li; Yunguang Li; Xiangyu Tang; Bingchuan Tian; Gongwei Wu; Jianfeng Xu; Xumiao Zhang; Feng Chen; Cheng Wang; Ennan Zhai; Yuhong Liao; Dennis Cai; Tao Lin;
33	SkeletonHunter: Diagnosing and Localizing Network Failures in Containerized Large Model Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unfortunately, these advantages render the network support for containerized large model training extremely challenging, due to the high dynamics of containers, the complex interplay between underlay and overlay networks, and the stringent requirements on failure detection and localization. Existing data center network debugging tools, which rely on comprehensive or opportunistic monitoring, are either inefficient or inaccurate in this setting.This paper presents SkeletonHunter, a container network monitoring and diagnosis system that leverages the intrinsic and regular sparsity of the network traffic incurred by large model training.	Wei Liu; Kun Qian; Zhenhua Li; Tianyin Xu; Yunhao Liu; Weicheng Wang; Yun Zhang; Jiakang Li; Shuhong Zhu; Xue Li; Hongfei Xu; Fei Feng; Ennan Zhai;
34	ByteTracker: An Agentless and Real-time Path-aware Network Probing System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose ByteTracker, the first agentless probing and diagnostic system for large-scale data center networks.	Shixian Guo; Kefei Liu; Yulin Lai; Yangyang Bai; Ziwei Zhao; Songlin Liu; Jianghang Ning; Gen Li; Jianwei Hu; Yongbin Dong; Feng Luo; Sisi Wen; Qi Zhang; Yuan Chen; Jiale Feng; Yang Bai; Chengcai Yao; Zhe Liu; Xin Hu; Yang Lv; Zhuo Jiang; Jiao Zhang; Tao Huang;
35	MixNet: A Runtime Reconfigurable Optical-Electrical Fabric for Distributed Mixture-of-Experts Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we advocate for a first-of-its-kind system, called MixNet, that unlocks topology reconfiguration during distributed MoE training.	Xudong Liao; Yijun Sun; Han Tian; Xinchen Wan; Yilun Jin; Zilong Wang; Zhenghang Ren; Xinyang Huang; Wenxue Li; Kin Fai Tse; Zhizhen Zhong; Guyue Liu; Ying Zhang; Xiaofeng Ye; Yiming Zhang; Kai Chen;
36	Orderlock: A New Type of Deadlock and Its Implications on High Performance Network Protocol Design Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, no practical implementation has successfully achieved all three simultaneously. We identify and prove that the simultaneous realization of these features constitutes a necessary and sufficient condition for a new type of deadlock, which we term Orderlock.	Weihao Jiang; Wenli Xiao; Yuqing Yang; Peirui Cao; Shizhen Zhao;
37	MegaScale-Infer: Efficient Mixture-of-Experts Model Serving with Disaggregated Expert Parallelism Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To fully exploit disaggregation in the presence of MoE’s sparsity, MegaScale-Infer introduces ping-pong pipeline parallelism, which partitions a request batch into micro-batches and shuttles them between attention and FFNs for inference.	Ruidong Zhu; Ziheng Jiang; Chao Jin; Peng Wu; Cesar A. Stuardo; Dongyang Wang; Xinlei Zhang; Huaping Zhou; Haoran Wei; Yang Cheng; Jianzhe Xiao; Xinyi Zhang; Lingjun Liu; Haibin Lin; Li-Wen Chang; Jianxi Ye; Xiao Yu; Xuanzhe Liu; Xin Jin; Xin Liu;
38	Astral: A Datacenter Infrastructure for Large Language Model Training at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The flourishing of Large Language Models (LLMs) calls for increasingly ultra-scale training. In this paper, we share our experience in designing, deploying, and operating our novel Astral datacenter infrastructure, along with operational lessons and evolutionary insights gained from its production use.	Qingkai Meng; Hao Zheng; Zhenhui Zhang; ChonLam Lao; Chengyuan Huang; Baojia Li; Ziyuan Zhu; Hao Lu; Weizhen Dang; Zitong Lin; Weifeng Zhang; Lingfeng Liu; Yuanyuan Gong; Chunzhi He; Xiaoyuan Hu; Yinben Xia; Xiang Li; Zekun He; Yachen Wang; Xianneng Zou; Kun Yang; Gianni Antichi; Guihai Chen; Chen Tian;
39	SGLB: Scalable and Robust Global Load Balancing in Commodity AI Clusters Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present SGLB, a distributed, global congestion-aware load balancing system for AI clusters.	Chenchen Qi; Wenfei Wu; Yongcan Wang; Keqiang He; Yu-Hsiang (Sean) Kao; Zongying He; Chen-Yu Yen; Zhuo Jiang; Feng Luo; Surendra Anubolu; Yanjin Gao; Bingfeng Lin; Wenda Ni; Yiming Yang; Donglin Wei; Boyang Zhou; Jian Wang; Shan Ding;
40	SyCCL: Exploiting Symmetry for Efficient Collective Communication Scheduling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose SyCCL, a scalable collective schedule synthesizer that aims to synthesize near-optimal schedules in tens of minutes for production-scale machine-learning jobs.	Jiamin Cao; Shangfeng Shi; Jiaqi Gao; Weisen Liu; Yifan Yang; Yichi Xu; Zhilong Zheng; Yu Guan; Kun Qian; Ying Liu; Mingwei Xu; Tianshu Wang; Ning Wang; Jianbo Dong; Binzhang Fu; Dennis Cai; Ennan Zhai;
41	Fornax: A Hardware-Centric Session Management in Large Public Cloud Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we advocate for a radical new mechanism to shift the management paradigm from software-centric architecture to hardware-centric architecture, which adopts session as the basic management unit and designs two-way protocols to facilitate the management process.	Heng Yu; Jian Wang; Jian Zhao; Kai Ren; Guozhi Lin; Baozeng Zhang; Yunpeng Guan; Xin Li; Hao Yin; Jiajun Liang; Liang Wang; Chao Pei; Yachen Wang; Xin Jin; Jilong Wang; Congcong Miao;
42	NPC: Rethinking Dataplane Through Network-aware Packet Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we revisit the network dataplane by integrating the network measurement module with the packet classification module.	Xinyi Zhang; Qianrui Qiu; Zhiyuan Xu; Peng He; Xilai Liu; Kav\'{e} Salamatian; Changhua Pei; Gaogang Xie;
43	Pegasus: A Universal Framework for Scalable Deep Learning Inference on The Dataplane Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the current use of the match-action table (MAT) abstraction on the dataplane is misaligned with DL inference, leading to several key limitations, including accuracy degradation, limited scale, and lack of generality. This paper proposes Pegasus to address these limitations.	Yinchao Zhang; Su Yao; Yong Feng; Kang Chen; Tong Li; Zhuotao Liu; Yi Zhao; Lexuan Zhang; Xiangyu Gao; Feng Xiong; Qi Li; Ke Xu;
44	PtCAM: Scalable High-Speed Name Prefix Lookup Using TCAM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a scheme to support generic hierarchical name lookups on millions of prefixes with fast, constant and guaranteed performance using ternary content-addressable memory (TCAM).	Tian Song; Tianlong Li; Yating Yang;
45	Scaling SCIERA: A Journey Through The Deployment of A Next-generation Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To accelerate innovation and deployments, our aim is to increase the number of native SCION use cases, where the application is fully SCION-aware and optimizes communication across all path choices offered by the network.	Fran\c{c}ois Wirz; Marten Gartner; Jelte van Bommel; Elham Ehsani Moghadam; Grace H. Cimaszewski; Anxiao He; Yizhe Zhang; Henry Birge-Lee; Felix Kottmann; Cyrill Kr\{a}henb\{u}hl; Jonghoon Kwon; Kyveli Mavromati; Liang Wang; Daniel Bertolo; Marco Canini; Buseung Cho; Ronaldo A. Ferreira; Simon Peter Green; David Hausheer; Junbeom Hur; Xiaohua Jia; Heejo Lee; Prateek Mittal; Omo Oaiya; Chanjin Park; Adrian Perrig; Jerry Sobieski; Yixin Sun; Cong Wang; Klaas Wierenga;
46	RANBooster: Democratizing Advanced Cellular Connectivity Through Fronthaul Middleboxes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, challenges such as achieving state-of-the-art performance and accessing data and control knobs hinder their widespread adoption. To address these issues, we propose a middlebox architecture, called RANBooster, that enhances the RAN capabilities without modifying existing network functions, by leveraging the open fronthaul interface.	Xenofon Foukas; Tenzin Samten Ukyab; Bozidar Radunovic; Sylvia Ratnasamy; Scott Shenker;
47	Understanding and Profiling CXL.mem Using PathFinder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: PathFinder leverages the capabilities of existing hardware performance monitors (PMUs) and dissects the CXL.mem protocol at adequate granularities. Our key idea is to view the server processor and its chipset as a multi-stage Clos network, equip each architectural module with a PMU-based telemetry engine, track different CXL.mem paths, and apply conventional traffic analysis techniques.	Xiao Li; Zerui Guo; Yuebin Bai; Mahesh Ketkar; Hugh Wilkinson; Ming Liu;
48	PreTE: Traffic Engineering with Predictive Failures Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our large-scale measurements of per-second optical-layer data reveal that the fiber’s failure probability increases by several orders of magnitude when experiencing a rare and ephemeral degradation state. Therefore, we present a novel traffic engineering (TE) system called PreTE to factor in the dynamic fiber cut probabilities directly into TE systems.	Congcong Miao; Zhizhen Zhong; Yiren Zhao; Arpit Gupta; Ying Zhang; Sirui Li; Zekun He; Xianneng Zou; Jilong Wang;
49	S2: A Distributed Configuration Verifier for Hyper-Scale Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, instead of further scaling up the verification limited to a single server, we study how to scale out the verification using the resources of multiple servers.	Dan Wang; Peng Zhang; Wenbing Sun; Wenkai Li; Xing Feng; Hao Li; Jiawei Chen; Weirong Jiang; Yongping Tang;
50	New Evolution of Hoyan: Enhancing Scalability, Usability, and Accuracy for Alibaba’s Global WAN Verification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, recent years have seen the emergence of new challenges in scalability, usability, and accuracy for Hoyan. This paper presents the new evolution of Hoyan to address these challenges.	Yifei Yuan; Fangdan Ye; Yifan Li; Jingkai Zhang; Mengqi Liu; Yuyang Sang; Ruizhen Yang; Duncheng She; Zhiqing Ye; Tianchen Guo; Xiaobo Zhu; Xinji Tang; Li Jia; Zhongyu Guan; Lingpeng Su; Ci Wang; Ruiyang Feng; Shuo Wu; Zhonghui Xie; Cheng Jin; Peng Zhang; Qing Ma; Xianlong Zeng; Dennis Cai; Ennan Zhai;
51	Lessons Learned from Operating A Large Network Telescope Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We develop and apply techniques to leverage third-party scanning activity to validate the integrity of the data, and to discover misconfigurations in the instrumentation.	Alexander M\{a}nnel; Jonas M\{u}cke; K. C. Claffy; Max Gao; Ricky K. P. Mok; Marcin Nawrocki; Thomas C. Schmidt; Matthias W\{a}hlisch;
52	Unlocking Superior Performance in Reconfigurable Data Center Networks with Credit-Based Transport Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Flare, a novel credit-based transport protocol that ensures reliable traffic delivery, low latency, and leverages the rapidly reconfiguring circuits of the RDCN to opportunistically route traffic over short paths, maximizing throughput.	Federico De Marchi; Jialong Li; Ying Zhang; Wei Bai; Yiting Xia;
53	From ATOP to ZCube: Automated Topology Optimization Pipeline and A Highly Cost-Effective Network Topology for Large Model Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To assist in exploring topology design, we propose ATOP, an Automated Topology Optimization Pipeline, which models network topology as a set of hyperparameters, enabling the discovery of potential topologies.	Zihan Yan; Dan Li; Li Chen; Dian Xiong; Kaihui Gao; Yiwei Zhang; Rui Yan; Menglei Zhang; Bochun Zhang; Zhuo Jiang; Jianxi Ye; Haibin Lin;
54	Reliable and Decentralized Certificate Revocation Via DNS: The Case for RevDNS Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present RevDNS, a DNS-based revocation scheme that drops CDN dependence while preserving real-time guarantees.	Taejoong Chung; Dave Levin; Protick Bhowmick;
55	SaTE: Low-Latency Traffic Engineering for Satellite Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores traffic engineering (TE) for large-scale Low-Earth-Orbit satellite constellations.	Hao Wu; Yizhan Han; Mohit Rajpal; Qizhen Zhang; Jingxian Wang;
56	Small-scale LEO Satellite Networking for Global-scale Demands Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We thus propose TinyLEO, a software-defined solution to shrink LEO network size for enormous global demands via dynamic spatiotemporal supply-demand matching.	Yuanjie Li; Yimei Chen; Jiabo Yang; Jinyao Zhang; Bowen Sun; Lixin Liu; Hewu Li; Jianping Wu; Zeqi Lai; Qian Wu; Jun Liu;
57	Direct-to-Cell Satellite Network Without Satellite Navigation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To enforce highly available, trustworthy, and roaming policy-compliant network services, they heavily rely on user geolocation and timing information from external global navigation satellite systems (GNSS) to assist with their radio access, authentication, and authorization. Our analysis and field tests reveal that, this cross-technology over-reliance propagates satellite navigation’s defects to direct-to-cell satellite networks, leading to diverse issues such as intermittent connectivity, over/under-billing, unauthorized services, and service denials even when direct-to-cell satellites are accessible.	Wei Liu; Yuanjie Li; Jingyi Lan; Hewu Li; Yimei Chen; Lixin Liu; Jiabo Yang; Xi Long; Li Ouyang; Minghao Tang; Jianping Wu; Qian Wu; Jun Liu; Zeqi Lai;
58	StarCDN: Moving Content Delivery Networks to Space Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The fundamental challenge in designing StarCDN lies in the orbital motion of satellites, which causes each satellite’s coverage area to change rapidly, serving vastly different regions (e.g., US and Europe) within minutes. To address this, we introduce new consistent hashing and relayed fetching schemes tailored to LEO satellite networks.	William X. Zheng; Aryan Taneja; Maleeha Masood; Anirudh Sabnis; Ramesh K. Sitaraman; Deepak Vasisht;
59	ByteScale: Communication-Efficient Scaling of LLM Training with A 2048K Context Length on 16384 GPUs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The mismatch between data heterogeneity and static mesh causes redundant communication and imbalanced computation, degrading the training efficiency.In this work, we introduce ByteScale, an efficient, flexible, and scalable LLM training framework for large-scale mixed training of long and short sequences.	Hao Ge; Junda Feng; Qi Huang; Fangcheng Fu; Xiaonan Nie; Lei Zuo; Haibin Lin; Bin Cui; Xin Liu;
60	Making Cellular Networks More Efficient By Roaming-in-Place Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Roaming-in-Place (RinP), a technique for dynamically sharing capacity across mobile network operators.	Tenzin Samten Ukyab; Lisa Suzuki; Demetrius Davis; Zhihong Luo; Silvery Fu; Shaddi Hasan; Sylvia Ratnasamy; Scott Shenker;
61	Enabling Over-the-Air AI for Edge Computing Via Metasurface-Driven Physical Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present MetaAI, a novel wireless computing paradigm that integrates neural network computation directly into wireless signal propagation.	Chao Feng; Shuo Liang; Chenghui Li; Gaoteng Zhao; Beier Jing; Yaxiong Xie; Xiaojiang Chen;
62	Towards Next-Generation Global IoT: Empowering Massive Connectivity with Harmonious Multi-Network Coexistence Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This problem cannot be resolved using conventional approaches and hinders the scaled deployment of LoRaWANs as a global IoT infrastructure. Based on our new findings, we propose design principles that guide our exploration for effective strategies to address this emerging practical problem.	Ziyue Zhang; Xianjin Xia; Ruonan Li; Yuanqing Zheng;
63	Mobile Underwater Backscatter Networking Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents EchoRider, the first system to enable reliable underwater backscatter networking under mobility.EchoRider introduces three key components.	Purui Wang; Sayed Saad Afzal; Fadel Adib;
64	Acoustic Backscatter Network for Vehicle Body-in-White Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel approach to monitor the Body in White (BiW), the fundamental metallic structure of a vehicle.	Weiguo Wang; Yuan He; Yadong Xie; Chuyue Xie; Yi Kai; Chengchen Hu;
65	Low-Overhead Distributed Application Observation with DeepTrace: Achieving Accurate Tracing in Production Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing non-intrusive solutions either have limited applicability or lack sufficient accuracy under high concurrency. To address these challenges, we propose DeepTrace, a transaction-based, non-intrusive distributed tracing framework designed for microservices.	Yantao Geng; Han Zhang; Zhiheng Wu; Yahui Li; Jilong Wang; Xia Yin;
66	Hummingbird: Fast, Flexible, and Fair Inter-Domain Bandwidth Reservations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To realize the long-standing vision of providing quality-of-service (QoS) guarantees on a public Internet, this paper introduces Hummingbird: a lightweight QoS-system that provides fine-grained inter-domain reservations for end hosts.Hummingbird enables flexible and composable reservations with end-to-end guarantees, and addresses an often overlooked, but crucial, aspect of bandwidth-reservation systems: incentivization of network providers.	Karl W\{u}st; Giacomo Giuliari; Markus Legner; Jean-Pierre Smith; Marc Wyss; Jules Bachmann; Juan Garcia-Pardo; Adrian Perrig;
67	Inter-domain Routing with Extensible Criteria Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We thus propose IREC, an inter-domain routing architecture for the SCION path-aware Internet architecture that enables path optimization with extensible criteria.	Seyedali Tabaeiaghdaei; Jelte van Bommel; Marc Wyss; Jo\~{a}o Luis Sobrinho; Giovanni Barbiero; Giacomo Giuliari; Ahad N. Zehmakan; Adrian Perrig;
68	Network Support For Scalable And High Performance Cloud Exchanges Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Financial exchanges are migrating to the public cloud, but the best-effort nature of the cloud fabric is at odds with the stringent networking requirements of the exchanges. We present Onyx, a system for meeting such requirements which uses many well-studied techniques in a new context as well as introduces new techniques that enable a scalable cloud financial exchange.	Muhammad Haseeb; Jinkun Geng; Daniel Duclos-Cavalcanti; Xiyu Hao; Ulysses Butler; Radhika Mittal; Srinivas Narayana; Anirudh Sivaraman;
69	Formalizing Dependence of Web Infrastructure Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a rigorous statistical metric for Internet centralization.	Rumaisa Habib; Kimberly Ruth; Gautam Akiwate; Zakir Durumeric;
70	Towards User-level QoE: Large-scale Practice in Personalized Optimization of Adaptive Video Streaming Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, aligning user-level Quality of Experience (QoE) with algorithmic optimization objectives remains an unresolved challenge. Therefore, we propose LingXi, the first large-scale deployed system for personalized adaptive video streaming based on user-level experience.	Lianchen Jia; Chao Zhou; Chaoyang Li; Jiangchuan Liu; Lifeng Sun;
71	TLadder: QoE-Centric Video Ladder Optimization with Playback Feedback at Billion Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, instead of developing yet another ABR algorithm, we optimize the bitrate ladder configuration, which constitutes the decision space of ABR, by developing a system called TLadder.TLadder explicitly maximizes the quality-of-experience (QoE) that a ladder is expected to incur, through a principled optimization framework with polynomial complexity and provable optimality.	Zhuqi Li; He Liu; Shenglan Huang; Baojin Geng; Jack Chen; Jialin Chen; Liyang Sun; Qianyun Ma; Peizhe Liu; Junjun Zhao; Yiting Liao; Jamie Chen; Qian Ma; Qiang Ma; Feng Qian;
72	ACE: Sending Burstiness Control for High-Quality Real-time Communication Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing approaches trying to smoothen the bitrate inevitably force an undesirable trade-off between latency and video quality. To address this, we propose a dual-control approach that manages both the encoding and transmission burstiness.	Xiangjie Huang; Jiayang Xu; Haiping Wang; Hebin Yu; Sandesh Dhawaskar Sathyanarayana; Shu Shi; Zili Meng;
73	Harnessing WebRTC for Large-Scale Live Streaming Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we report our deployment experiences comprehensively.	Wei Zhang; Tong Meng; Xianhua Zeng; Wei Yang; Changqing Yan; Chao Li; Chenguang Li; Feng Qian; Junfeng Yang; Lei Zhang; Zhi Wang;
74	Scalable Video Conferencing Using SDN Principles Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our main insight, discerned from dissecting the operation of production SFU servers, is that SFUs largely mimic traditional packet-processing operations such as dropping and forwarding. Guided by this, we present Scallop, an SDN-inspired SFU that decouples video-conferencing applications into a hardware-based data plane for latency-sensitive and frequent media operations, and a software control plane for the (infrequent) remaining tasks, such as analyzing feedback signals and session management.	Oliver Michel; Satadal Sengupta; Hyojoon Kim; Ravi Netravali; Jennifer Rexford;
75	Coflow Scheduling for LLM Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present Hermod, a comprehensive coflow scheduler that orchestrates all coflow types for LLM training.	Xinchen Wan; Xinyu Yang; Kaiqiang Xu; Xudong Liao; Yilun Jin; Yijun Sun; Zhenghang Ren; Han Tian; Kai Chen;
76	HardMesh: Enabling High-performance Service Mesh Ingress Processing with SmartNICs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In response, we propose HardMesh, a hardware-software hybrid ingress gateway that leverages a Smart-NIC for high-performance traffic analysis and efficient traffic routing.	Myoungsung You; Jaehyun Nam; Minjae Seo; Taejune Park; Seungwon Shin;
77	SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces SpliDT, a scalable framework that reimagines DT deployment as a partitioned inference problem over a sliding window of packets (Figure 1).	Murayyiam Parvez; Annus Zulfiqar; Roman Beltiukov; Shir Landau Feibish; Walter Willinger; Arpit Gupta; Muhammad Shahbaz;
78	Carbon- and Precedence-Aware Scheduling for Data Processing Clusters Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we show that carbon-aware scheduling for data processing benefits from knowledge of both time-varying carbon and precedence constraints.	Adam Lechowicz; Rohan Shenoy; Noman Bashir; Mohammad Hajiesmaili; Adam Wierman; Christina Delimitrou;
79	HACK: Homomorphic Acceleration Via Compression of The Key-Value Cache for Disaggregated LLM Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Homomorphic Acceleration via Compression of the KV cache (HACK) for disaggregated LLM inference.	Zeyu Zhang; Haiying Shen; Shay Vargaftik; Ran Ben Basat; Michael Mitzenmacher; Minlan Yu;
80	Designing Transport-Level Encryption for Datacenter Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents SDP, a protocol design for emerging datacenter transports, such as NDP and Homa, to integrate data encryption.	Tianyi Gao; Xinshu Ma; Suhas Narreddy; Eugenio Luo; Steven Chien; Michio Honda;
81	ZooRoute: Enhancing Cloud-Scale Network Reliability Via Overlay Proactive Rerouting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents ZooRoute, a tenant-transparent, fast failure recovery service that requires no modifications to physical devices.	Xiaoqing Sun; Xionglie Wei; Xing Li; Ju Zhang; Bowen Yang; Yi Wang; Ye Yang; Yu Qi; Le Yu; Chenhao Jia; Zhanlong Zhang; Xinyu Chen; Jianyuan Lu; Shize Zhang; Enge Song; Yang Song; Tian Pan; Rong Wen; Biao Lyu; Yang Xu; Shunmin Zhu;
82	Achieving High-Speed and Robust Encrypted Traffic Anomaly Detection with Programmable Switches Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we design and implement Mazu, an inline network intrusion detection system with programmable switches specifically developed to protect data centers connecting to the internet service provider.	Han Zhang; Guyue Liu; Xingang Shi; Yahui Li; Dongbiao He; Jilong Wang; Zhiliang Wang; Yongqing Zhu; Ke Ruan; Weihua Cao; Xia Yin;
83	Palladium: A DPU-enabled Multi-Tenant Serverless Cloud Over Zero-copy Multi-node RDMA Fabrics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present Palladium, a DPU-offloaded serverless data plane enabling distributed zero-copy communication.	Shixiong Qi; Songyu Zhang; K. K. Ramakrishnan; Diman Zad Tootaghaj; Hardik Soni; Puneet Sharma;
84	Threading The Ocean: Mapping Digital Routes Across Submarine Cables Using Calypso Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Calypso, a new framework that leverages traceroute data to map traffic to submarine cables.	Caleb Wang; Ying Zhang; Qianli Dong; Esteban Carisimo; Ramakrishnan Durairajan; Fabi\'{a}n E. Bustamante;
85	AoRA: AI-on-RAN for Backhaul-free Edge Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present AoRA, the first framework realizing the AI-on-RAN vision by dynamically utilizing available computational headroom in GPU- and NPU-accelerated RAN platforms to deliver AI services directly from within the base stations.	Siyavushkhon Kholmatov; Seongsik Cho; Song Chong; Kyunghan Lee;
86	NIER: Practical Neural-enhanced Low-bitrate Video Conferencing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present NIER, a video conferencing system that can adaptively maintain a low bitrate (e.g., 10–100 Kbps) with reasonable visual quality while being robust to packet losses.	Anlan Zhang; Yuming Hu; Chendong Wang; Yu Liu; Zejun Zhang; Haoyu Gong; Ahmad Hassan; Shichang Xu; Zhenhua Li; Bo Han; Feng Qian;
87	Discovering Millions of New Nodes and Links in The Internet By Challenging The Uniformity Assumption in Multipath Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel system BayMuDA, that can estimate LBR distributions and calculate the minimum number of probes needed to statistically discover all nodes and links within a given hop.	Zhongxu Guan; Shuai Wang; Li Chen; Zhaoteng Yan; Jiaye Lin; Dan Li; Yong Jiang; Yingxin Wang; Ziqian Liu;
88	Wisely Optimizing Short Video Streaming for A User-Vendor Win-Win Outcome Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a framework that intelligently reduces streaming data consumption without compromising user experience.	Jinlong E; Wei Xu; Jianfei Bi; Lin He; Haoyang Li; Anqi Gu; Dan Yang; Yunpeng Chai;