徐飞

• 2009.09~2014.06    Ph.D. in Computer Science and Technology    Huazhong University of Science and Technology    Supervisor: Prof. Hai Jin; co-supervisor: Prof. Fangming Liu
  

• 2007.09~2009.07    M.Eng. in Communication and Information System    Huazhong University of Science and Technology

• 2003.09~2007.07    B.Eng. in Communication Engineering    Huazhong University of Science and Technology

• 2024.01~至今          3044AM永利    3044AM永利    教授

• 2017.01~2023.12    3044AM永利    3044AM永利    副教授

• 2014.07~2016.12    3044AM永利    3044AM永利    晨晖学者（团队博士后）

徐飞，博士，3044AM永利教授，博士生导师，本科教学副经理，研究方向为云计算和分布式系统。分别于2007年、2009年和2014年获得华中科技大学学士、硕士和博士学位。现为中国计算机学会（CCF）高级会员，分布式计算与系统专业委员会执行委员，3044AM永利首任CCF传播大使，曾任上海市计算机学会存储专业委员会副主任。主持国家自然科学基金面上/青年项目、上海市科委重点项目、腾讯基础平台技术犀牛鸟专项研究计划项目等，在P IEEE、IEEE TC、TPDS、TSC、TMC、Infocom、MLSys、Mobicom、SIGMETRICS、ICPP等国际重要期刊或会议上发表论文50余篇，申请授权国家发明专利10余项。先后获得湖北省优秀博士学位论文奖、ACM武汉暨湖北省计算机学会优秀博士学位论文奖、CCFSys 2023 Best Student Paper、第27届ACM ChinaSys最佳Poster展示奖等学术奖励。

NEWS

• Our paper entitled “Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling” (open-sourced on GitHub) has been accepted by MLSys 2025 (A leading conference at the intersection of Machine Learning and Systems). (Feb. 2025)

• Our deep learning job scheduler - Rubick (open-sourced on GitHub) has received the 27th ACM SIGOPS ChinaSys Best Poster Presentation Award. (Dec. 2024)

• Our paper entitled “Espresso: Cost-Efficient Large Model Training by Exploiting GPU Heterogeneity in the Cloud” (open-sourced on GitHub) has been accepted by IEEE Infocom 2025 (CCF-A). (Dec. 2024)

• Our research group is currently recruiting PhD students for the 2025 intake. Students interested in pursuing research in MLSys, distributed systems, and edge intelligence are welcome to contact me at (fxu@cs.ecnu.edu.cn). 课题组正在招收25级博士研究生，请有志于从事MLSys、分布式系统和边缘智能研究的同学尽快与我（fxu@cs.ecnu.edu.cn）联系。（Dec. 2024）

• 中国计算机学会分布式计算与系统专业委员会执行委员，3044AM永利首任CCF传播大使，CCF高级会员; 曾任上海市计算机学会存储专业委员会副主任 (2019年10月-2023年1月).

• Program Committee Member for The International Workshop on Intelligent Cloud Computing and Networking (ICCN 2020 and ICCN 2019), held in conjunction with IEEE INFOCOM; The International Conference on Informatics and Computing (PIC 2018, PIC 2017, PIC 2016).

• Volunteer Committee Member for The ACM Turing 50th Celebration Conference - China (ACM TURC 2017, ACM图灵奖五十年中国大会), held in Shanghai, China, May 12-14, 2017.

• Publication Chair, Web Chair, and Program Committee Member for The 11th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2015), held in Wuhan, China, Nov. 10-11, 2015.

• Web Chair for The 9th International Conference on Green, Pervasive and Cloud Computing (GPC 2014), held in Wuhan, China, May 26-28, 2014.

• Invited Reviewer for IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Dependable and Secure Computing, Journal of Parallel and Distributed Computing, IEEE Systems Journal, Concurrency and Computation: Practice and Experience, Journal of Supercomputing, Cluster Computing, 计算机学报, 中国科学: 信息科学.

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1. Distributed Machine Learning Systems (分布式机器学习系统):

• Efficient job scheduling for LLM training and inference in deep learning clusters

• Communication scheduling optimization for distributed machine learning

• Task scheduling for performance optimization of DAG-style data analytics

2. Predictable Cloud Computing (云计算性能保证): 

• Resource (VMs & serverless functions) provisioning for predictable performance in the cloud

• Performance measurements, modeling, and optimization of representative cloud workloads (distributed DNN training, big data analytics, NoSQL databases, etc.)

• Live migration of virtual machines and containers

3. Collaborative Cloud-Edge-Client Computing (云边端协同计算): 

• Interference-aware and user-unaware container migrations

• Heterogeneous resource (GPU/other accelerators) management in cloud-edge-client systems
  

• Energy-efficient mobile Web browser

Doctoral Dissertation: Towards Predictable Performance in IaaS Clouds: Performance Optimization and Scheduling of Virtual Machine Workloads (面向IaaS 云计算的虚拟机负载性能优化与保证机制研究), April 18, 2014.

• March 2016, Won 2015  Excellent Doctoral Dissertation Award in Hubei Province (获得2015年度湖北省优秀博士学位论文奖).

• May 2015, Won 2015 ACM Wuhan & Hubei Computer Society Doctoral Dissertation Award (获得2015年度ACM武汉&湖北省计算机学会优秀博士论文奖).

My Google Scholar Citation Webpage

• COMS0031131051.01, Database Systems: Principles and Implementation (数据库系统原理与实践), 2023-2025, East China Normal University

• COMS0031131019.02, Principles of Database System (数据库系统原理), 2015-2023, East China Normal University （获2022年华为公司-教育部产学合作协同育人新工科建设项目 —— 结合国产化GaussDB云数据库开展课程教学） 

• COMS0031131021.02, Database Systems Laboratory (数据库系统实践), 2016-2023, East China Normal University

• COMS0031132803.01, Mobile Application Development (移动应用开发), 2016-2025, East China Normal University

• COMS0031132054, Information System Modeling and Design (信息系统建模与设计), 2014, 2017, East China Normal University

My Students

Master Students

• 2025级：Deshang Re（任德上）；Yuanbin Xu（徐袁斌）；Xueru Bai（拜雪茹）

• 2024级：Yikun Gu（顾一坤）；Linxuan Weng（翁凌璇）；Zongqing Wei（魏宗庆）；Xiang Shen（沈翔）；Ziang Huang（黄子昂）

• 2023级：Zhuoyan Bai（白卓岩）

• 2022级：

  -Xinyi Zhang（张欣怡），graduated in Summer 2025 and works in ByteDance, Shanghai（字节跳动）

  -Qiannan Zhou（周倩男），graduated in Summer 2025 and works in Tencent Inc., Shanghai（腾讯）

• 2021级：

  -Jiabin Chen（陈佳彬），graduated in Summer 2024 and works in Xiaomi, Wuhan（小米）

  -Aodong Chen（陈奥东），graduated in Summer 2024 and works in Tencent Inc., Shenzhen（腾讯）

• 2020级：

  -Ruitao Shang（尚睿涛），获3044AM永利优秀毕业生，graduated in Summer 2023 and works in Industrial Bank, Shanghai（兴业银行，管培生）

  -Xiyue Shen（沈希乐），graduated in Spring 2023 and works in NetEase, Hangzhou（网易游戏雷火工作室）

• 2019级：

  -Jianian Xu（徐家年），graduated in Summer 2022 and works in AMD, Shanghai (上海AMD研发中心)

• 2018级：

  -Yiling Qin（秦伊玲），获3044AM永利优秀毕业生，graduated in Summer 2021 and works in Intel, Shanghai（英特尔）

  -Qiang Qi（齐强），获3044AM永利优秀毕业生，graduated in Summer 2021 and works in China Unipay（中国银联）

• 2017级：

  -Haoyue Zheng（郑皓月）, 获国家奖学金, 上海市优秀毕业生, graduated in Summer 2020 and works in Ctrip, Shanghai（上海携程）

  -Wujie Shao（邵武杰）, graduated in Spring 2020 and works in Ele.me, Shanghai（饿了么）

• 2016级：

  -Huan Jiang（蒋欢）, graduated in Spring 2019 and works in China Merchants Bank, Chongqing（招商银行重庆分行）

• 2015级：

  -Shuai Yang（杨帅）, graduated in Summer 2018 and works in Ctrip, Shanghai（上海携程）

• 2013级：

  -Wangying Ye（叶王颖, co-supervised with Prof. Wei Zhang）, graduated in Spring 2016 and works in Works Applications, Shanghai (上海万革始软件应用软件有限公司)

Undergraduate Students

• 2021级：李锐星（3044AM永利优秀毕业生），任德上，邱臻，庞子珂.

• 2020级：顾一坤，董园（上海市优秀毕业生），杨润东.

• 2019级：白卓岩（上海市优秀毕业生），钟爱，生志翔.

• 2018级：张欣怡（3044AM永利优秀毕业生），汪子凡（上海市优秀毕业生），刘蓓嘉，范睿霖.

• 2017级：徐梓翔，向梦麟，周璇，巢祯麟.

• 2016级：张臻炜（3044AM永利校级优秀本科生毕业论文），陈前嘉，乐巍.

• 2015级：张伦.

• 2014级：秦伊玲（上海海事大公司级优秀本科生毕业论文），赖俊宇，陈圆，李天.

• 2013级：汪雨薇（3044AM永利校级优秀本科生毕业论文），郑皓月，王晓晨，田琪，江雯.

• 2012级：沈荣慧，穆月涵.

  
  

本科生创新创业项目

• DevAgent（基于MCP的端云协同开发智能体，2025-2026）——许乐；冯顾炜；程籽实.

• SmartAlarm2.0（基于云端协同的智能闹钟APP开发，2024-2025）——李治纬；应昊天；顾一坤.
  

• SmartAlarm（智能闹钟：让闹钟更懂你的睡眠，2023-2024）——邱臻；王华超；白卓岩；张甲伟；袁艺轩.

• ECNU Online Debug（老员工在线编程学习和答疑平台，2022-2023）——俞心如；杨睿；林嘉辉.

• MAPO：基于微信小程序的恋爱出行记录APP（2020-2021）——李雨倩；喻美玲；范睿霖；沈安如.

• ECNULostFound v2.0（丢了么2.0—基于微信小程序的线上失物招领平台，2019-2020）—— 陈雨；陈前嘉；汪春雨；高思宇. 获中国高校计算机大赛-2020微信小程序应用开发赛华东赛区二等奖.

• ECNULostFound（丢了么—华师大失物招领微信小程序，2018-2019）—— 陈前嘉；汪春雨. 获2019年上海市计算机应用能力大赛决赛二等奖；获2019年（第12届）中国老员工计算机设计大赛三等奖.

• Spot Price Modeling（2016-2017） —— 王晓晨；方品.

• iSecWiFi（面向无线网络安全的Wi-Fi集成化管理助手，2015-2016） —— 刘禹含；汪雨薇；韩杰枫.

• NSFC国家自然科学基金面上项目 (The National Natural Science Foundation of China), No.62372184, Efficient Multi-Dimensional Resource Allocation and Scheduling Optimizations for Heterogeneous Deep Learning Clusters (面向异构深度学习集群的高效多维度资源配置与调度优化方法研究), Principal Investigator, 01/2024 – 12/2027.

• NSFC国家自然科学基金面上项目 (The National Natural Science Foundation of China), No.61972158, Towards Predictable Deep Learning: Cost-Effective Cloud Resource Provisioning and Performance Optimization (面向可预测深度学习的高效益云资源配置与性能优化机制研究), Principal Investigator, 01/2020 – 12/2023.

• 上海市科委“科技创新行动计划”高新技术领域项目, No.20511102802, 面向可预测性能的虚拟化资源配置技术研究, Principal Investigator, 11/2020 – 10/2022.

• 2020腾讯基础平台技术犀牛鸟专项研究计划, 面向多租户NoSQL存储性能保证的负载调度及公平计价方法研究, Principal Investigator, 10/2020 – 10/2021.

• 上海市科委“科技创新行动计划”高新技术领域项目（重点项目）, No.17511102602, 面向性能干扰感知的网络业务实时迁移技术研究, Principal Investigator,06/2017-06/2019.

• NSFC国家自然科学基金青年项目 (The National Natural Science Foundation of China), No.61502172, Towards Predictable Performance in IaaS clouds: Elastic Resource Provisioning and Cost Efficiency Optimization (面向IaaS云性能保证的资源弹性配置及其性价比优化研究), Principal Investigator, 01/2016 – 12/2018.

• 中国博士后科学基金特别资助 (The Postdoctoral Science Foundation of China), No.2016T90353, Towards Predictable Performance and Optimal Cost-Effective Resource Provisioning in IaaS Clouds (面向IaaS 云性能保证的性价比最优资源租用方法研究), Principal Investigator, 08/2016 – 08/2018.

• 中国博士后科学基金面上资助 (一等资助) (The Postdoctoral Science Foundation of China), No.2015M580307, Achieving Application-level Utility Max-min Fairness of Bandwidth Allocation Based on Flow Aggregation in Datacenter Networks (基于云应用流聚合的效用公平带宽分配方法研究), Principal Investigator, 12/2015 － 12/2017.

Journal Papers:

• Aodong Chen, Fei Xu*, Li Han, Yuan Dong, Li Chen, Zhi Zhou, Fangming Liu, “Opara: Exploiting Operator Parallelism for Expediting DNN Inference on GPUs,” IEEE Transactions on Computers, 2025, 74(1): 325-333. DOI: 10.1109/TC.2024.3475589. (CCF A, Source codes)

• Yong Peng, Fei Xu*, Zongqing Wei, Shuohao Lin, Zhi Zhou, Miao Zhang, “U²CMigration: User-Unaware Container Migration with Predictive Analysis of Memory Dirty Pages,” Journal of Computer Science and Technology, 2025. DOI: 10.1007/s11390-025-4583-0. (CCF-T1, Source codes)

• Fei Xu*, Xiyue Shen, Shuohao Lin, Li Chen, Zhi Zhou, Fen Xiao, Fangming Liu, “Tetris: Proactive Container Scheduling for Long-Term Load Balancing in Shared Clusters,” IEEE Transactions on Services Computing, 2024, 17(5): 2918-2930. DOI: 10.1109/TSC.2024.3442544. (CCF A, Source codes)

• Kongyange Zhao, Zhi Zhou*, Lei Jiao, Shen Cai, Fei Xu, Xu Chen, “Taming Serverless Cold Start of Cloud Model Inference with Edge Computing,” IEEE Transactions on Mobile Computing, 2024, 23(8):8111-8128. DOI: 10.1109/TMC.2023.3348165. (CCF A)

• Fei Xu*, Jianian Xu, Jiabin Chen, Li Chen, Ruitao Shang, Zhi Zhou, Fangming Liu, “iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud,” IEEE Transactions on Parallel and Distributed Systems, 2023, 34(3): 812-827. DOI: 10.1109/TPDS.2022.3232715 (CCF A, Source codes)

• Fei Xu*, Yiling Qin, Li Chen, Zhi Zhou, Fangming Liu, “λDNN: Achieving Predictable Distributed DNN Training with Serverless Architectures,” IEEE Transactions on Computers, 2022, 71(2): 450-463. DOI:10.1109/TC.2021.3054656. (CCF A. Source codes)

• Abeda Sultana, Md. Mainul Haque, Li Chen*, Fei Xu, Xu Yuan, “Eiffel: Efficient and Fair Scheduling in Adaptive Federated Learning,” IEEE Transactions on Parallel and Distributed Systems, 2022, 33(12):4282-4294. (CCF A)

• Jananie Jarachanthan, Li Chen*, Fei Xu, Bo Li, “Astrea: Auto-Serverless Analytics towards Cost-Efficiency and QoS-Awareness,” IEEE Transactions on Parallel and Distributed Systems, 2022, 33(12):3833-3849. (CCF-A)

• Lin Jia, Zhi Zhou*, Fei Xu, Hai Jin, “Cost-Efficient Continuous Edge Learning for Artificial-Intelligence-of-Things (AIoT),” IEEE Internet of Things Journal, 2022, 9(10): 7325-7337. DOI: 10.1109/JIOT.2021.3104089 (SCI index, 一区)

• Bin Gao, Zhi Zhou, Fangming Liu*, Fei Xu, Bo Li, “An Online Framework for Joint Network Selection and Service Placement in Mobile Edge Computing”, IEEE Transactions on Mobile Computing, 2022, 21(10): 3836-3851. DOI: 10.1109/TMC.2021.3064847. (CCF A)

• Qiang Qi, Fei Xu*, Li Chen, Zhi Zhou, “Rationing Bandwidth Resources for Mitigating Network Resource Contention in Distributed DNN Training Clusters,” CCF Transactions on High Performance Computing, 2021, 3(2): 171-185. DOI:10.1007/s42514-021-00064-x. (ESCI index, 中国期刊, CCF C)

• Xinli Huang, Peng Shi, Yufei Liu, Fei Xu*, “Towards Trusted and Efficient SDN Topology Discovery: A Lightweight Topology Verification Scheme,” Computer Networks, 2020, 170: 107-119. (CCF B)

• Fei Xu*, Haoyue Zheng, Huan Jiang, Wujie Shao, Haikun Liu, Zhi Zhou, “Cost-Effective Cloud Server Provisioning for Predictable Performance of Big Data Analytics,” IEEE Transactions on Parallel and Distributed Systems, 2019, 30(5): 1036-1051. (CCF A. Source codes)
  

• Fei Xu*, Wangying Ye, Yuhan Liu, Wei Zhang,  “UFalloc: Towards Utility Max-min Fairness of Bandwidth Allocation for Applications in Datacenter Networks,” Mobile Networks and Applications (MONET), 2017, 22(2): 161-173. (SCI index, 二区)

• Fei Xu, Fangming Liu*, Hai Jin, “Heterogeneity and Interference-Aware Virtual Machine Provisioning for Predictable Performance in the Cloud,” IEEE Transactions on Computers, 2016, 65(8): 2470-2483. (CCF A)

• Fei Xu, Fangming Liu*, Peng Yin, Hai Jin, “Network-Aware Task Assignment for MapReduce Applications in Shared Clusters,” Journal of Internet Technology, 2015, 16(2): 325-333. (SCI index)

• Fei Xu, Fangming Liu*, Hai Jin, Athanasios V.Vasilakos, “Managing Performance Overhead of Virtual Machines in Cloud Computing: A Survey, State of Art and Future Directions,” Proceedings of the IEEE, 2014, 102(1): 11-31. (CCF A. ESI Highly Cited Paper)

• Fei Xu, Fangming Liu*, Linghui Liu, Hai Jin, Bo Li, Baochun Li, “iAware: Making Live Migration of Virtual Machines Interference-Aware in the Cloud,” IEEE Transactions on Computers, 2014, 63(12): 3012-3025. (CCF A)

Conference Papers:

• Qiannan Zhou, Fei Xu*, Linxuan Weng, Ruixing Li, Xudong Wu, Li Chen, Zhi Zhou, Fangming Liu, “Espresso: Cost-Efficient Large Model Training by Exploiting GPU Heterogeneity in the Cloud,” in Proc. of IEEE Infocom 2025, May 19-22, 2025. (CCF A, acceptance ratio: 272 / 1458 = 18.7%. Source codes)

• Xinyi Zhang, Hanyu Zhao, Wencong Xiao, Xianyan Jia, Fei Xu*, Yong Li, Wei Lin, Fangming Liu, “Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling,” in Proc. of MLSys 2025, May 12-15, 2025. (A leading conference at the intersection of Machine Learning and Systems. Source codes)

• Jianxiong Liao, Juntao Li, Zhi Zhou*, Fei Xu, Fangming Liu, Xu Chen, “Microns: Connection Subsetting for Microservices in Shared Clusters,” in Proc. of ACM SIGMETRICS 2025, June 9-13, 2025. Article No. 26. (CCF-B)

• Changlong Li, Zongwei Zhu*, Chao Wang, Fangming Liu, Fei Xu, Edwin H. -M. Sha, Xuehai Zhou, “Archer: Adaptive Memory Compression with Page-Association-Rule Awareness for High-Speed Response of Mobile Devices,” in Proc. of USENIX FAST 2025, February 25-27, 2025. pp. 497-511. (CCF-A)

• Jiabin Chen, Fei Xu*, Yikun Gu, Li Chen, Fangming Liu, Zhi Zhou, “HarmonyBatch: Batching multi-SLO DNN Inference with Heterogeneous Serverless Functions,” in Proc. of IEEE/ACM IWQoS 2024, June 19-21, 2024. pp. 1-10. (CCF B, acceptance ratio: 81 /326 = 24.8%. Source codes)

• Abeda Sultana, Fei Xu, Xu Yuan, Li Chen*, Nian-Feng Tzeng, “Hadar: Heterogeneity-Aware Optimization-Based Online Scheduling for Deep Learning Cluster,” in Proc. of IEEE IPDPS 2024, May 27-31, 2024. pp. 681-691. (CCF B)

• Md Sirajul Islam, Simin Javaherian, Fei Xu, Xu Yuan, Li Chen*, Nian-Feng Tzeng, “FedClust: Tackling Data Heterogeneity in Federated Learning through Weight-Driven Client Clustering,” in Proc. of ICPP 2024, August 12-15, 2024. pp. 474-483. (CCF B)

• Hao Bao, Zhi Zhou*, Fei Xu, Xu Chen, “COUPLE: Orchestrating Video Analytics on Heterogeneous Mobile Processors,” in Proc. of IEEE ICDE 2024, May 13-17, 2024. pp. 1561-1574. (CCF A)

• Ruitao Shang, Fei Xu*, Zhuoyan Bai, Li Chen, Zhi Zhou, Fangming Liu, “spotDNN: Provisioning Spot Instances for Predictable Distributed DNN Training in the Cloud,” in: Proc. of IEEE/ACM IWQoS 2023, June 19-21, 2023. pp. 1-10. (CCF B, acceptance ratio: 62 / 264 = 23.5%. Source codes)

• Jananie Jarachanthan, Li Chen*, Fei Xu, “ACTS: Autonomous Cost-Efficient Task Orchestration for Serverless Analytics,” in: Proc. of IEEE/ACM IWQoS 2023, June 19-21, 2023. (CCF B, acceptance ratio: 62 / 264 = 23.5%)

• Qingyuan Wang, Bin Gao*, Zhi Zhou*, Fei Xu, Chenghao Ouyang, “DAG-Aware Optimization for Geo-Distributed Data Analytics,” in: Proc. of ICPP 2023, August 7-10, 2023. pp. 472-481. (CCF B)

• Hao Bao, Zhi Zhou*, Jiajie Xie, Qianyi Huang, Fei Xu, Xu Chen, “COUPLE: Accelerating Video Analytics on Heterogeneous Mobile Processors,” in: Proc. of ACM MobiCom 2023, October 2-6, 2023. pp.1552-1554. (CCF A, Poster)

• Zhenwei Zhang, Qiang Qi, Ruitao Shang, Li Chen, Fei Xu*, “Prophet: Speeding up Distributed DNN Training with Predictable Communication Scheduling,” in: Proc. of ICPP 2021, August 9-12, 2021. Article No. 69. (CCF B, acceptance ratio: 87 / 329 = 26.4%. Source codes)

• Jananie Jarachanthan, Li Chen*, Fei Xu, Bo Li, “AMPS-Inf: Automatic Model Partitioning for Serverless Inference with Cost Efficiency,” in: Proc. of ICPP 2021, August 9-12, 2021. Article No. 14. (CCF B, acceptance ratio: 87 / 329 = 26.4%)

• Jananie Jarachanthan, Li Chen*, Fei Xu, Bo Li, “Astra: Autonomous Serverless Analytics with Cost-Efficiency and QoS-Awareness,” in: Proc. of IPDPS 2021 (Virtual), May 17-21, 2021. pp. 756-765. (CCF B)

• Abeda Sultana, Li Chen*, Fei Xu, Xu Yuan, “E-LAS: Design and Analysis of Completion-Time Agnostic Scheduling for Distributed Deep Learning Cluster,” in: Proc. of ICPP 2020 (Virtual), Edmonton, AB, Canada, August 17-20, 2020. Article No. 21. (CCF B)

• Haoyue Zheng, Fei Xu*, Li Chen, Zhi Zhou, Fangming Liu, “Cynthia: Cost-Efficient Cloud Resource Provisioning for Predictable Distributed Deep Neural Network Training,” in: Proc. of ICPP 2019, Kyoto, Japan, August 5-8, 2019. Article No. 86. (CCF B, acceptance ratio: 26%, 106 accepted papers out of 405 submitted full papers)
  

• Wujie Shao, Fei Xu*, Li Chen, Haoyue Zheng, Fangming Liu, “Stage Delay Scheduling: Speeding up DAG-style Data Analytics Jobs with Resource Interleaving,” in: Proc. of ICPP 2019, Kyoto, Japan, August 5-8, 2019. Article No. 8. (CCF B, acceptance ratio: 26%, 106 accepted papers out of 405 submitted full papers. Source codes)

• Yiling Qin, Lun Zhang, Fei Xu*, Daidong Luo, “Interference and Topology-Aware VM Live Migrations in Software-Defined Networks,” in: Proc. of HPCC 2019, Zhangjiajie, China, August 10-12, 2019. pp. 1068-1075. (CCF C)

• Bin Gao, Zhi Zhou, Fangming Liu*, Fei Xu, “Winning at the Starting Line: Joint Network Selection and Service Placement for Mobile Edge Computing,” in: Proc. of INFOCOM 2019, Paris, France, April 29-May 2, 2019. pp. 1459-1467. (CCF A, acceptance ratio: 19.7%)

• Fei Xu*, Shuai Yang, Zhi Zhou, Jia Rao, “eBrowser: Making Human-Mobile Web Interactions Energy Efficient with Event Rate Learning,” in: Proc. of ICDCS 2018 (Research Track), Vienna, Austria, July 2-5, 2018. pp. 523-533. (CCF B, 78 accepted papers out of 378 submitted full papers, acceptance ratio: ~20%. Source codes)

• Fei Xu*, Huan Jiang, Haoyue Zheng, Wujie Shao, “iSpot: Achieving Predictable Performance for Big Data Analytics with Cloud Transient Servers,” in: Proc. of ISPA 2017, Guangzhou, China, December 12-15, 2017. pp. 314-321. (CCF C)

• Jue Chen, Jinbang Chen*, Fei Xu*, Min Yin, Wei Zhang, “When Software Defined Networks Meet Fault Tolerance: A Survey,” in: Proc. of ICA3PP 2015, Zhangjiajie, China, November 18-20, 2015. pp. 351-368. (CCF C)

• Wangying Ye, Fei Xu*, Wei Zhang, “Achieving Application-Level Utility Max-min Fairness of Bandwidth Allocation in Datacenter Networks,” in: Proc. of CollaborateCom 2015, Wuhan, China, November 10-11, 2015. pp. 36-46. (CCF C)

• Fei Xu, Fangming Liu*, Dekang Zhu, Hai Jin, “Boosting MapReduce with Network-Aware Task Assignment,” in: Proc. of CloudComp 2013, Wuhan, China, October 17-19, 2013. pp. 79-89.

• Fei Xu, Hai Jin*, Xiaofei Liao, Fei Qiu, “Enhancing the Reliability of SIP Service in Large-Scale P2P-SIP Networks,” in: Proc. of GPC 2011, Oulu, Finland, May 11-13, 2011. pp. 52-61.

Patents and Software Copyrights:

• 徐飞, 周倩男. 一种面向云端异构GPU集群的大模型训练资源配置优化方法. 专利申请号202411922113.7, 专利申请日期2024年12月25日.

• 徐飞, 陈奥东. 基于DNN算子并行的深度学习推理加速方法. 专利申请号202311157590.4, 专利申请日期2023年09月08日. 专利授权日期2025年8月12日.

• 徐飞, 尚睿涛. 一种面向NoSQL云数据库资源使用的计费方法. 专利申请号202210414913.2, 专利申请日期2022年04月20日. 专利授权日期2024年10月29日.

• 徐飞, 徐家年. 深度学习推理性能干扰感知的GPU资源配置方法. 专利申请号202210295359.0, 专利申请日期2022年03月24日.

• 徐飞, 齐强. 一种基于网络带宽分配的分布式深度学习性能优化方法. 专利申请号202010932914.7, 专利申请日期2020年09月08日. 专利授权日期2022年08月05日.

• 徐飞, 蒋欢. 一种作业性能预测方法、装置、介质、设备及系统. 专利申请号201810443167.3, 专利申请日期2018年05月10日. 专利授权日期2020年12月22日.

• 徐飞, 杨帅. 一种基于手势事件频率学习的手机浏览器功耗节约方法. 专利申请号201810105376.7, 专利申请日期2018年02月02日. 专利授权日期2020年11月20日.

• 金海, 刘方明, 徐飞, 刘凌辉. 多维度资源性能干扰感知的虚拟机在线迁移方法及系统. 专利申请号201310115244.X, 专利申请日期2013年04月03日, 专利授权日期2016年04月20日.

• 金海, 刘方明, 徐飞, 刘凌辉. 多维度资源性能干扰感知的虚拟机在线迁移系统. 软著登字第0598801, 软件著作版权登记号2013SR093039, 登记时间2013年08月31日.

• 金海, 郭峰江, 廖小飞, 蒋洪磊, 徐飞, 钱力, 舒畅. 一种保证VoIP系统动态中转可靠性的方法. 专利申请号201010278215.1, 专利申请日期2010年09月10日, 专利授权日期2013年05月22日.

• 金海, 舒畅, 廖小飞, 蒋洪磊, 徐飞, 钱力, 郭峰江. 一种VoIP系统中的语音动态中转方法. 专利申请号201010277706.4, 专利申请日期2010年09月10日, 专利授权日期2012年11月14日.

• 金海, 舒畅, 廖小飞, 蒋洪磊, 徐飞, 钱力, 邱飞, 郭峰江. 一种VoIP系统中信令的传输方法. 专利申请号201010278213.2, 专利申请日期2010年09月10日, 专利授权日期2012年09月07日.

Open-Source Projects on ECNU-iCloud's GitHub: Espresso; Rubick; iGniter; Tetris; Opara; HarmonyBatch; lambdaDNN; Prophet; iSpot; eBrowser; DelayStage