Publications

You can find my Google Scholar Citations here.

Note on the author list: Underlined are students/interns working with me.

Conference and Workshop Proceedings

2024

Zhifeng Jiang, Peng Ye, Shiqi He, Wei Wang, Ruichuan Chen, and Bo Li, ‘‘Lotto: Secure Participant Selection against Adversarial Servers in Federated Learning,’’ in the Proceedings of USENIX Security Symposium (Security ’24), Philadelphia, PA, USA, August 2024.

Ruibo Fan, Wei Wang, and Xiaowen Chu, ‘‘DTC-SpMM: Bridging the Gap in Accelerating General Sparse Matrix Multiplication with Tensor Cores,’’ in the Proceedings of ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS ’24), San Diego, CA, USA, April-May 2024.

Nan Yan, Yuqing Li, Jing Chen, Xiong Wang, Jianan Hong, Kun He, and Wei Wang, ‘‘Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning’’, in the Proceedings of IEEE INFOCOM ’24, Vancouver, Canada, May 2024.

Zhifeng Jiang, Wei Wang, and Ruichuan Chen, ‘‘Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy,’’ in the Proceedings of ACM European Conference on Computer Systems (EuroSys ’24), Athens, Greece, April 2024.

2023

Suyi Li, Wei Wang, Jun Yang, Guangzhen Chen, and Daohe Lu, ‘‘Golgi: Performance-Aware, Resource-Efficient Function Scheduling for Serverless Computing,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’23), Santa Cruz, CA, USA, October-November 2023. (Best Paper Award)

Qizhen Weng*, Lingyun Yang*, Yinghao Yu, Wei Wang, Xiaochuan Tang, Guodong Yang, and Liping Zhang, ‘‘Beware of Fragmentation: Scheduling GPU-Sharing Workloads with Fragmentation Gradient Descent,’’ in the Proceedings of USENIX Annual Technical Conference (ATC ’23), Boston, MA, USA, July 2023. (*Equal contribution)

Lin Zhang, Shaohuai Shi, Xiaowen Chu, Wei Wang, Bo Li, and Chengjian Liu, ‘‘DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining,’’ in the Proceedings of the 43rd IEEE International Conference on Distributed Computing Systems (ICDCS ’23), Hong Kong, China, July 2023.

Ruibo Fan, Wei Wang, and Xiaowen Chu, ‘‘Fast Sparse GPU Kernels for Accelerated Training of Graph Neural Networks,’’ in the Proceedings of the 37th IEEE International Parallel and Distributed Processing Symposium (IPDPS ’23), St. Petersburg, FL, USA, May 2023.

Mingzhe Li, You Lin, Jin Zhang, and Wei Wang, ‘‘CoChain: High Concurrency Blockchain Sharding via Consensus on Consensus,’’ in the Proceedings of IEEE INFOCOM ’23, New York area, USA, May 2023.

Minchen Yu, Tingjia Cao, Wei Wang, and Ruichuan Chen, ‘‘Following the Data, Not the Function: Rethinking Function Orchestration in Serverless Computing,’’ in the Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’23), Boston, MA, April 2023. [Technical Report]

2022

Zhifeng Jiang, Wei Wang, Baochun Li, and Bo Li, ‘‘Pisces: Efficient Federated Learning via Guided Asynchronous Training,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’22), San Francisco, CA, November 2022.

Huangshi Tian, Suyi Li, Ao Wang, Wei Wang, Tianlong Wu, and Haoran Yang, ‘‘Owl: Performance-Aware Scheduling for Resource-Efficient Function-as-a-Service Cloud,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’22), San Francisco, CA, November 2022. [Technical Report]

Yongkang Zhang, Yinghao Yu, Wei Wang, Qiukai Chen, Jie Wu, Zuowei Zhang, Jiang Zhong, Tianchen Ding, Qizhen Weng, Lingyun Yang, Cheng Wang, Jian He, Guodong Yang, and Liping Zhang, ‘‘Workload Consolidation in Alibaba Clusters: The Good, the Bad, and the Ugly,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’22), San Francisco, CA, November 2022.

Mingzhe Li, You Lin, Jin Zhang, and Wei Wang, ‘‘Jenga: Orchestrating Smart Contracts in Sharding-Based Blockchain for Efficient Processing,’’ in the Proceedings of IEEE International Conference on Distributed Computing Systems (ICDCS ’22), Bologna, Italy, July 2022.

Qizhen Weng, Wencong Xiao, Yinghao Yu, Wei Wang, Cheng Wang, Jian He, Yong Li, Liping Zhang, Wei Lin, and Yu Ding, ‘‘MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters,’’ in the Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’22), Renton, WA, April 2022.

Da Yan, Wei Wang, and Xiaowen Chu, ‘‘POSTER: An LLVM-based Open-Source Compiler for NVIDIA GPUs,’’ poster paper in ACM Symposium on Principles and Practice of Parallel Programming (PPoPP ’22), Seoul, South Korea, February 2022.

2021

Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, and Feng Yan, ‘‘Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’21), Seattle, WA, November 2021.

Luping Wang*, Lingyun Yang*, Yinghao Yu, Wei Wang, Bo Li, Xianchao Sun, Jian He, and Liping Zhang, ‘‘Morphling: Fast, Near-Optimal Auto-Configuration for Cloud-Native Model Serving,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’21), Seattle, WA, November 2021. (*Equal contribution)

Suyi Li*, Luping Wang*, Wei Wang, Yinghao Yu, and Bo Li, ‘‘George: Learning to Place Long-Lived Containers in Large Clusters with Operation Constraints,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’21), Seattle, WA, November 2021. (*Equal contribution)

Huangshi Tian, Minchen Yu, and Wei Wang, ‘‘CrystalPerf: Learning to Characterize the Performance of Dataflow Computation through Code Analysis,’’ in the Proceeds of USENIX Annual Technical Conference (ATC ’21), Virtual Conference, July 2021.

Minchen Yu, Zhifeng Jiang, Hok Chun Ng, Wei Wang, Ruichuan Chen, and Bo Li, ‘‘Gillis: Serving Large Neural Networks in Serverless Functions with Automatic Model Partitioning,’’ in the Proceedings of the 41st IEEE International Conference on Distributed Computing Systems (ICDCS ’21, Research Track), Virtual Conference, July 2021. (Best Paper Runner Up)

Chen Chen, Hong Xu, Wei Wang, Baochun Li, Bo Li, Li Chen, and Gong Zhang, ‘‘Communication-Efficient Federated Learning with Adaptive Parameter Freezing,’’ in the Proceedings of the 41st IEEE International Conference on Distributed Computing Systems (ICDCS ’21, Research Track), Virtual Conference, July 2021.

Da Yan, Wei Wang, and Xiaowen Chu, ‘‘POSTER: Simplifying Low-Level GPU Programming with GAS,’’ in the Proceedings of ACM Symposium on Principles and Practice of Parallel Programming (PPoPP ’21), Virtual Conference, February 2021.

2020

Luping Wang*, Qizhen Weng*, Wei Wang, Chen Chen, and Bo Li, ‘‘Metis: Learning to Schedule Long-Running Applications in Shared Container Clusters at Scale,’’ in the Proceedings of IEEE/ACM International Conference for High Performance Computing, Networking, Storage, and Analysis (SC20), Virtual Conference, November 2020. (*Equal contribution)

Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, and Bo Li, ‘‘Semi-Dynamic Load Balancing: Efficient Distributed Learning in Non-Dedicated Environments,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’20), Virtual Conference, October 2020.

Chengliang Zhang, Suyi Li, Junzhe Xia, Wei Wang, Feng Yan, and Yang Liu, ‘‘BatchCrypt: Efficient Homomorphic Encryption for Cross-Silo Federated Learning,’’ in the Proceedings of USENIX Annual Technical Conference (ATC ’20), Virtual Conference, July 2020.

Minchen Yu, Yinghao Yu, Yunchuan Zheng, Baichen Yang, and Wei Wang, ‘‘RepBun: Load-Balanced, Shuffle-Free Cluster Caching for Structured Data,’’ in the Proceedings of IEEE INFOCOM ’20, Virtual Conference, July 2020.

Jun Yi, Chengliang Zhang, Wei Wang, Cheng Li, and Feng Yan, ‘‘Not All Explorations are Equal: Harnessing Heterogeneous Profiling Cost for Efficient MLaaS Training,’’ in the Proceedings of IEEE International Parallel and Distributed Processing Symposium (IPDPS ’20), Virtual Conference, May 2020.

Da Yan, Wei Wang, and Xiaowen Chu, ‘‘Demystifying Tensor Cores to Optimize Half-Precision Matrix Multiply,’’ in the Proceedings of IEEE International Parallel and Distributed Processing Symposium (IPDPS ’20), Virtual Conference, May 2020.

Da Yan, Wei Wang, and Xiaowen Chu, ‘‘Optimizing Batched Winograd Convolution on GPUs,’’ in the Proceedings of ACM Symposium on Principles and Practice of Parallel Programming (PPoPP ’20), San Diego, CA, February 2020.

2019

Suyi Li, Yong Cheng, Yang Liu, Wei Wang, and Tianjian Chen, ‘‘Abnormal Client Behavior Detection in Federated Learning,’’ in the Proceedings of the 2nd International Workshop on Federated Learning for Data Privacy and Confidentiality, in Conjunction with NeurIPS 2019 (FL-NeurIPS ’19), Vancouver, Canada, December 2019.

Huangshi Tian, Yunchuan Zheng, and Wei Wang, ‘‘Characterizing and Synthesizing Task Dependencies of Data-Parallel Jobs in Alibaba Cloud,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’19), Santa Cruz, CA, November 2019. [Trace Generator for DAG-Structured Jobs]

Huangshi Tian, Qizhen Weng, and Wei Wang, ‘‘Towards Framework-Independent, Non-Intrusive Performance Characterization for Dataflow Computation,’’ in the Proceedings of ACM SIGOPS Asia-Pacific Workshop on Systems (APSys ’19), Hangzhou, China, August 2019.

Chengliang Zhang, Minchen Yu, Wei Wang, and Feng Yan, ‘‘MArk: Exploiting Cloud Services for Cost-Effective, SLO-Aware Machine Learning Inference Serving,’’ in the Proceedings of USENIX Annual Technical Conference (ATC ’19), Renton, WA, July 2019.

Luping Wang, Wei Wang, and Bo Li, ‘‘CMFL: Mitigating Communication Overhead for Federated Learning,’’ in the Proceedings of the 39th IEEE International Conference on Distributed Computing Systems (ICDCS ’19, Research Track), Dallas, TX, July 2019. [Technical Report]

Yinghao Yu, Wei Wang, Jun Zhang, and Khaled B. Letaief, ‘‘LACS: Load-Aware Cache Sharing with Isolation Guarantee,’’ in the Proceedings of the 39th IEEE International Conference on Distributed Computing Systems (ICDCS ’19, Research Track), Dallas, TX, July 2019.

Chen Chen, Wei Wang, and Bo Li, ‘‘Round-Robin Synchronization: Mitigating Communication Bottlenecks in Parameter Servers,’’ in the Proceedings of IEEE INFOCOM ’19, Paris, France, April 2019.

2018

Yuechen Tao, Jingjie Jiang, Shiyao Ma, Luping Wang, Wei Wang, and Bo Li, ‘‘Unraveling the RTT-fairness Problem for BBR: A Queueing Model,’’ in the Proceedings of IEEE GLOBECOM ’18, Abu Dhabi, UAE, December 2018.

Mingzhe Li, Jin Zhang, and Wei Wang, ‘‘Task Selection and Scheduling for Food Delivery: A Game-theoretic Approach,’’ in the Proceedings of IEEE GLOBECOM ’18, Abu Dhabi, UAE, December 2018.

Yinghao Yu, Renfei Huang, Wei Wang, Jun Zhang, and Khaled B. Letaief, ‘‘SP-Cache: Load-balanced, Redundancy-free Cluster Caching with Selective Partition,’’ in the Proceedings of IEEE/ACM International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, TX, November 2018.

Huangshi Tian, Minchen Yu, and Wei Wang, ‘‘Continuum: A Platform for Cost-Aware, Low-Latency Continual Learning,’’ in the Proceedings of ACM Symposium on Cloud Computing (SoCC ’18), Carlsbad, CA, October 2018. [Technical Report]

Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, and Bo Li, ‘‘Fast Distributed Deep Learning via Worker-adaptive Batch Sizing,’’ poster paper in ACM Symposium on Cloud Computing (SoCC ’18, Poster Session), Carlsbad, CA, October 2018.

Chengliang Zhang, Huangshi Tian, Wei Wang, and Feng Yan, ‘‘Stay Fresh: Speculative Synchronization for Fast Distributed Machine Learning,’’ in the Proceedings of the 38th IEEE International Conference on Distributed Computing Systems (ICDCS ’18, Research Track), Vienna, Austria, July 2018.

Yinghao Yu, Wei Wang, Jun Zhang, Qizhen Weng, and Khaled B. Letaief, ‘‘OpuS: Fair and Efficient Cache Sharing for In-Memory Data Analytics,’’ in the Proceedings of the 38th IEEE International Conference on Distributed Computing Systems (ICDCS ’18, Research Track), Vienna, Austria, July 2018.

Luping Wang and Wei Wang, ‘‘Fair Coflow Scheduling without Prior Knowledge,’’ in the Proceedings of the 38th IEEE International Conference on Distributed Computing Systems (ICDCS ’18, Research Track), Vienna, Austria, July 2018.

Luping Wang, Wei Wang, and Bo Li, ‘‘Utopia: Near-optimal Coflow Scheduling with Isolation Guarantee,’’ in the Proceedings of IEEE INFOCOM ’18, Honolulu, HI, April 2018. [Technical Report]

Chen Chen, Wei Wang, and Bo Li, ‘‘Performance-Aware Fair Scheduling: Exploiting Demand Elasticity of Data Analytics Jobs,’’ in the Proceedings of IEEE INFOCOM ’18, Honolulu, HI, April 2018.

2017

Yinghao Yu, Wei Wang, Jun Zhang, and Khaled B. Letaief, ‘‘LERC: Coordinated Cache Management for Data-Parallel Systems,’’ in the Proceedings of IEEE GLOBECOM ’17 (Big Data Track), Singapore, December 2017.

Luping Wang, Wei Wang, and Bo Li, ‘‘Towards Online Checkpointing Mechanism for Cloud Transient Servers,’’ in the Proceedings of IEEE GLOBECOM ’17 (Big Data Track), Singapore, December 2017.

Chen Chen, Wei Wang, and Bo Li, ‘‘Speculative Slot Reservation: Enforcing Service Isolation for Dependent Data-Parallel Computations,’’ in the Proceedings of the 37th IEEE International Conference on Distributed Computing Systems (ICDCS ’17, Research Track), Atlanta, GA, June 2017.

Chen Chen, Wei Wang, Shengkai Zhang, and Bo Li, ‘‘Cluster Fair Queueing: Speeding up Data-Parallel Jobs with Delay Guarantees,’’ in the Proceedings of IEEE INFOCOM ’17, Atlanta, GA, May 2017.

Yinghao Yu, Wei Wang, Jun Zhang, and Khaled B. Letaief, ‘‘LRC: Dependency-Aware Cache Management for Data Analytics Clusters,’’ in the Proceedings of IEEE INFOCOM ’17, Atlanta, GA, May 2017.

Wei Wang, Shiyao Ma, Bo Li, and Baochun Li, ‘‘Coflex: Navigating the Fairness-Efficiency Tradeoff for Coflow Scheduling,’’ in the Proceedings of IEEE INFOCOM ’17, Atlanta, GA, May 2017.

2016

Wei Wang and A-Long Jin, ‘‘Friends or Foes: Revisiting Strategy-Proofness in Cloud Network Sharing,’’ in the Proceedings of the IEEE International Conference on Network Protocols (ICNP ’16), Singapore, November 2016. [Technical Report]

Wei Wang, Baochun Li, Ben Liang, and Jun Li, ‘‘Multi-Resource Fair Sharing for Datacenter Jobs with Placement Constraints,’’ in the Proceedings of the IEEE/ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SC16), Salt Lake City, UT, November 2016. [Technical Report]

Wei Wang, Baochun Li, Ben Liang, and Jun Li, ‘‘Towards Multi-Resource Fair Allocation with Placement Constraints,’’ poster paper in the Proceedings of the 2016 ACM International Conference on Measurement and Modeling of Computer Science (SIGMETRICS ’16, Poster Session), Antibes Juan-les-Pins, France, June 2016.

2015 and Earlier

Wei Wang, Chen Feng, Baochun Li, and Ben Liang, ‘‘On the Fairness-Efficiency Tradeoff for Packet Processing with Multiple Resources,’’ in the Proceedings of the 10th ACM SIGCOMM International Conference on emerging Networking EXperiments and Technologies (CoNEXT ’14), Sydney, Australia, December 2014. [Technical Report, Slides]

Wei Wang, Baochun Li, and Ben Liang, ‘‘Dominant Resource Fairness in Cloud Computing Systems with Heterogeneous Servers,’’ in the Proceedings of IEEE INFOCOM ’14, Toronto, Canada, April 2014. [Full Version, Slides]

Wei Wang, Ben Liang, and Baochun Li, ‘‘Low Complexity Multi-Resource Fair Queueing with Bounded Delay,’’ in the Proceedings of IEEE INFOCOM ’14, Toronto, Canada, April 2014. [Technical Report, Slides]

Wei Wang, Baochun Li, and Ben Liang, ‘‘Multi-Resource Round Robin: A Low Complexity Packet Scheduler with Dominant Resource Fairness,’’ in the Proceedings of the 21st IEEE International Conference on Network Protocols (ICNP ’13), Göttingen, Germany, October 2013. [Technical Report, Slides]

Wei Wang, Baochun Li, and Ben Liang, ‘‘To Reserve or Not to Reserve: Optimal Online Multi-Instance Acquisition in IaaS Clouds,’’ in the Proceedings of the 10th USENIX International Conference on Autonomic Computing (ICAC ’13), San Jose, CA, June 2013. (Best Paper Award Finalist) [Technical Report, Slides]

Wei Wang, Ben Liang, and Baochun Li, ‘‘Multi-Resource Generalized Processor Sharing for Packet Processing,’’ in the Proceedings of the 21st ACM/IEEE International Symposium on Quality of Service (IWQoS ’13), Montreal, Canada, June 2013. [Slides]

Wei Wang, Ben Liang, and Baochun Li, ‘‘Revenue Maximization with Dynamic Auctions in IaaS Cloud Markets,’’ in the Proceedings of the 21st ACM/IEEE International Symposium on Quality of Service (IWQoS ’13), Montreal, Canada, June 2013. (Short Paper) [Technical Report, Slides]

Wei Wang, Di Niu, Baochun Li, and Ben Liang, ‘‘Dynamic Cloud Resource Reservation via Cloud Brokerage,’’ in the Proceedings of the 33rd International Conference on Distributed Computing Systems (ICDCS ’13), Philadelphia, PA, July 2013. [Technical Report, Slides]

Wei Wang, Ben Liang, and Baochun Li, ‘‘On Fairness-Efficiency Tradeoffs for Multi-Resource Packet Processing,’’ in the Proceedings of IEEE ICDCS Workshop on Data Center Performance (DCPerf), Philadelphia, PA, July 2013. (Invited Paper) [Slides]

Wei Wang, Baochun Li, and Ben Liang, ‘‘Towards Optimal Capacity Segmentation with Hybrid Cloud Pricing,’’ in the Proceedings of the 32nd International Conference on Distributed Computing Systems (ICDCS ’12), Macau, China, June 2012. [Technical Report, Slides]

Wei Wang, Baochun Li, and Ben Liang, ‘‘District: Embracing Local Markets in Truthful Spectrum Double Auctions,’’ in the Proceedings of the 8th IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON ’11), Salt Lake City, UT, June 2011. [Slides]

Qingjiang Shi, Chen He, Hongyang Chen, Lingge Jiang, and Wei Wang, ‘‘Sequential Greedy Localization in Wireless Sensor Networks with Inaccurate Anchor Positions,’’ in the Proceedings of IEEE GLOBECOM ’09, Honolulu, HI, December 2009.

Wei Wang and Chen He, ‘‘A Noncooperative Spectrum Sensing Game with Maximum Network Throughput,’’ in the Proceedings of IEEE GLOBECOM ’09, Honolulu, HI, December 2009.

Journal Articles

Mingzhe Li, Wei Wang, and Jin Zhang, ‘‘Towards Efficient and Deposit-Free Blockchain-Based Spatial Crowdsourcing,’’ to appear in ACM Transactions on Sensor Networks (TOSN), March 2024.

Shijie Zhang, Jiang Xiao, Enping Wu, Feng Cheng, Bo Li, Wei Wang, and Hai Jin, ‘‘MorphDAG: A Workload-Aware Elastic DAG-based Blockchain,’’ to appear in IEEE Transactions on Knowledge and Data Engineering (TKDE), March 2024.

Chen Chen, Hong Xu, Wei Wang, Baochun Li, Bo Li, Li Chen, and Gong Zhang, ‘‘Synchronize Only the Immature Parameters: Communication-Efficient Federated Learning By Freezing Parameters Adaptively,’’ to appear in IEEE Transactions on Parallel and Distributed Systems (TPDS), January 2023.

Mingzhe Li, Wei Wang, and Jin Zhang, ‘‘LB-Chain: Load-Balanced and Low-Latency Blockchain Sharding via Account Migration,’’ to appear in IEEE Transactions on Parallel and Distributed Systems (TPDS), January 2023.

Chen Chen, Hong Xu, Wei Wang, Baochun Li, Bo Li, Li Chen, and Gong Zhang, ‘‘GIFT: Towards Accurate and Efficient Federated Learning with Gradient-Instructed Frequency Tuning,’’ to appear in IEEE Journal on Selected Areas in Communications (JSAC), Special Issue on Communication-Efficient Distributed Learning over Networks, First Quarter, 2023.

Lin Zhang, Shaohuai Shi, Wei Wang, and Bo Li, ‘‘Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning,’’ to appear in IEEE Transactions on Cloud Computing (TCC), September 2022.

Chengliang Zhang, Minchen Yu, Wei Wang, and Feng Yan, ‘‘Enabling Cost-Effective, SLO-Aware Machine Learning Inference Serving on Public Cloud,’’ IEEE Transactions on Cloud Computing (TCC), vol. 10, no. 3, pp. 1765-1779, July-September 2022.

Zhifeng Jiang, Wei Wang, Bo Li, and Qiang Yang, ‘‘Towards Efficient Synchronous Federated Training: A Survey on System Optimization Strategies,’’ accepted to appear in IEEE Transactions on Big Data (TBD), May 2022.

Mingzhe Li, Wei Wang, Jin Zhang, and Qian Zhang, ‘‘Incentivizing WiFi-based Multilateration Location Verification,’’ IEEE Internet of Things Journal (IoT-J), vol. 9, no. 4, pp. 3083-3096, February 2022.

Yinghao Yu, Chengliang Zhang, Wei Wang, Jun Zhang, and Khaled Ben Letaief, ‘‘Towards Dependency-Aware Cache Management for Data Analytics Applications,’’ IEEE Transactions on Cloud Computing (TCC), vol. 10, no. 1, pp. 706-723, January-March 2022.

Jun Li, Wei Song, Yongbin Gao, Huixing Wang, Yier Yan, Bo Huang, Jun Zhang, and Wei Wang, ‘‘Monocular 3D Object Detection based on Depth Guided Local Convolution for Smart Payment in D2D systems,’’ accepted to appear in IEEE Internet of Things Journal (IoT-J), November 2021.

Mingzhe Li, Jingrou Wu, Wei Wang, and Jin Zhang, ‘‘Towards Privacy-Preserving Task Assignment for Fully Distributed Spatial Crowdsourcing,’’ IEEE Internet of Things Journal (IoT-J), vol. 8, no. 18, pp. 13991-14002, September 2021.

Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, and Bo Li, ‘‘Accelerating Distributed Learning in Non-Dedicated Environments,’’ accepted to appear in IEEE Transactions on Cloud Computing (TCC), July 2021.

Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Chengjian Liu, Wei Wang, and Bo Li, ‘‘A Quantitative Survey of Communication Optimizations in Distributed Deep Learning,’’ IEEE Network Magazine, vol. 35, no. 3, pp. 230-237, May-June 2021.

Yinghao Yu, Wei Wang, Renfei Huang, Jun Zhang, and Khaled Ben Letaief, ‘‘Achieving Load-Balanced, Redundancy-Free Cluster Caching with Selective Partition,’’ IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 31, no. 2, pp. 439-454, February 2020.

Wei Wang, Ben Liang, and Baochun Li, ‘‘Optimal Online Multi-Instance Acquisition in IaaS Clouds,’’ IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 26, no. 12, pp. 3407-3419, December 2015.

Wei Wang, Ben Liang, and Baochun Li, ‘‘Multi-Resource Fair Allocation in Heterogeneous Cloud Computing Systems,’’ IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 26, no. 10, pp. 2822-2835, October 2015.

Wei Wang, Di Niu, Ben Liang, and Baochun Li, ‘‘Dynamic Cloud Instance Acquisition via IaaS Cloud Brokerage,’’ IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 26, no. 6, pp. 1580-1593, June 2015.

Wei Wang, Ben Liang, and Baochun Li, ‘‘Designing Truthful Spectrum Double Auctions with Local Markets,’’ IEEE Transactions on Mobile Computing (TMC), vol. 13, no. 1, pp. 75-88, January 2014. [Supplementary Document]

Preprints

Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, and Feng Yan,‘‘Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX,’’ arXiv::2105.01281, 2021.

Shiyao Ma, Jingjie Jiang, Wei Wang, and Bo Li, ‘‘Fairness of Congestion-Based Congestion Control: Experimental Evaluation and Analysis,’’ arXiv:1706.09115, 2017.

Wei Wang, Ben Liang, and Baochun Li, ‘‘On Low Complexity Multi-Resource Packet Scheduling with Dominant Resource Fairness.’’ (This is the full version of our ICNP 2013 paper.)