LI

NS

research
group

Learning, Incentives, and Optimization
for Networked Systems

T. Kim, J. Zuo, X. Zhang and C. Joe-Wong, Edge-MSL: Split Learning on the Mobile Edge via Multi-Armed Bandits, accepted to IEEE INFOCOM 2024.

Y. Li, L. Su, C. Joe-Wong, E. Yeh and S. Ioannidis, Distributed Experimental Design Networks, accepted to IEEE INFOCOM 2024.

J. Chen, T. Lan and C. Joe-Wong, RGMComm: Return Gap Minimization via Discrete Communications in Multi-Agent Reinforcement Learning, accepted to AAAI 2024.

W. Liu, X. Zhang, J, Duan, C. Joe-Wong, Z. Zhou and X. Chen, DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset, accepted to IEEE Transactions on Mobile Computing. Preliminary version appeared in IEEE/ACM IWQoS 2023.

M. Siew, S. Sharma, K. Guo, D. Cai, W. Wen, C. Joe-Wong and T. Q. S. Quek, Towards Effective Resource Procurement in MEC: a Resource Re-selling Framework, accepted to IEEE Transactions on Services Computing.

X. Zhang, J. Zuo, Z. Huang, Z. Zhou, X. Chen and C. Joe-Wong, Learning with Side Information: Elastic Multi-resource Control for the Open RAN, IEEE Journal on Selected Areas in Communications.

R. Sahay, S. Nicoll, M. Zhang, T.-Y. Yang, C. Joe-Wong, K. A. Douglas and C. G. Brinton, Predicting Learning Interactions in Social Learning Networks: A Deep Learning Enabled Approach, IEEE/ACM Transactions on Networking. Preliminary version appeared in IEEE INFOCOM 2017.

T. Kim, S. Sathyanarayana, S. Chen, Y. Im, X. Zhang, S. Ha and C. Joe-Wong, MoDEMS: Optimizing Edge Computing for User Mobility, IEEE Journal on Selected Areas in Communications. Preliminary versions appeared at IEEE INFOCOM 2022 and as a poster in IEEE IWQoS 2021.

I.-C. Lin, O. Yağan and C. Joe-Wong, Dynamic Coupling Strategy for Interdependent Network Systems Against Cascading Failures, IEEE Transactions on Network Science and Engineering.

M. M. Kamani, Y. Yao, H. Lyu, Z. Cheng, L. Chen, L. Li, C. Joe-Wong and J. Luo, Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking, NeurIPS Datasets and Benchmarks Track 2023.

Y. Yao, W. Jin, S. Ravi and C. Joe-Wong, FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks, NeurIPS 2023. Preliminary version appeared in FedGraph 2022.

Y. Liu, L. Su, C. Joe-Wong, S. Ioannidis, E. Yeh and M. Siew, Cache-Enabled Federated Learning Systems, ACM MobiHoc 2023.

S. Lin, X. Zhang, Y. Li, C. Joe-Wong, J. Duan and X. Chen, EdgeC3: Online Management for Edge-Cloud Collaborative Continuous Learning, IEEE SECON 2023. Preliminary version appeared as a poster in ACM APNET 2023.

Y. Hu, J. Zuo, B. Iannucci and C. Joe-Wong, Intelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learning, IEEE SECON 2023.

H. Jiang, X. Zhang and C. Joe-Wong, DOLL: Distributed OnLine Learning using Preemptible Cloud Instances, IEEE/IFIP WiOpt 2023. Preliminary version appeared in MAMA 2022.

R. Bostandoost, B. Sun, C. Joe-Wong and M. Hajiesmaili, Near-optimal Online Algorithms for Joint Pricing and Scheduling in EV Charging Networks, Best Paper Candidate at ACM E-Energy 2023.

W. Wu, X. Zhang, J. Duan, C. Joe-Wong, Z. Zhou and X. Chen, AdaCoOpt: Leverage the Interplay of Batch Size and Aggregation Frequency for Federated Learning, Best Paper Candidate at IEEE/ACM IWQoS 2023. Preliminary version appeared in FogML 2023.

Y. Hu, C. Zhang, E. Andert, H. Singh, A. Shrivastava, J. Laudon, Y. Zhou, B. Iannucci and C. Joe-Wong, GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing, MLSys 2023.

X. Liu*, J. Zuo*, H. Xie, C. Joe-Wong and J. C. S. Lui, Variance-Adaptive Algorithm for Probabilistic Maximum Coverage Bandits with General Feedback, IEEE INFOCOM 2023. *Equal contribution

I.-C. Lin, O. Yağan and C. Joe-Wong, Evaluating the Optimality of Dynamic Coupling Strategies in Interdependent Network Systems, IEEE ICC 2023.

Y. Yao, M. Mahdi Kamani, E. Cheng, L. Chen, C. Joe-Wong and T. Liu, FedRule: Federated Rule Recommendation System with Graph Neural Networks, ACM/IEEE IoTDI 2023. Preliminary version appeared in the Workshop on Federated Learning: Recent Advances and New Challenges, held in conjunction with NeurIPS 2022.

T. Kim, S. Singh, N. Madaan and C. Joe-Wong, Characterizing Internal Evasion Attacks in Federated Learning, AISTATS 2023. Preliminary version won the Best Student Poster Award at CrossFL 2022.

M. T. Siew, S. Sharma and C. Joe-Wong, ACRE: Actor Critic Reinforcement Learning for Failure-Aware Edge Computing Migrations, CISS 2023.

T. Kim, J. Li, S. Singh, N. Madaan and C. Joe-Wong, Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning, BUGS 2023, held in conjunction with NeurIPS 2023.

W. Jin, Y. Yao, S. Han, C. Joe-Wong, S. Ravi, S. Avestimehr and C. He, FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System, International Workshop on Federated Learning in the Age of Foundation Models, held in conjunction with NeurIPS 2023.

W. Wu, X. Zhang, J. Duan, C. Joe-Wong, Z. Zhou and X. Chen, Federated Learning at the Edge: An Interplay of Mini-batch Size and Aggregation Frequency, FOGML 2023, held in conjunction with IEEE INFOCOM 2023.

M. T. Siew, S. Arunasalam, Y. Ruan, Z. Zhu, L. Su, S. Ioannidis, E. Yeh and C. Joe-Wong, Poster Abstract: Fair Training of Multiple Federated Learning Models on Resource Constrained Network Devices, Best Poster Award at ACM/IEEE IPSN 2023.

S. Lin, X. Zhang, Y. Li, C. Joe-Wong, J. Duan and X. Chen, An Online Control Approach of Collaborative Federated Learning with Constrained Resources, poster at ACM APNET 2023.

X. Zhang, S. Chen, Y. Zhang, Y. Im, M. Gorlatova, S. Ha and C. Joe-Wong, Optimal Network Protocol Selection for Competing Flows via Online Learning, IEEE Transactions on Mobile Computing, March 2022. Preliminary version appeared in IEEE ICNP 2019.

M. Khayatian, M. Mehrabian, E. Andert, R. Grimsley, K. Liang, Y. Hu, I. McCormack, C. Joe-Wong, J. Aldrich, B. Iannucci and A. Shrivastava, Plan B - Design Methodology for Cyber-Physical Systems Robust to Timing Failures, ACM Transactions on Cyber-Physical Systems.

X. Liu, J. Zuo, S. Wang, C. Joe-Wong, J. C. S. Lui and W. Chen, Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms, NeurIPS 2022.

J. Zuo, S. Hu, T. Yu, S. Li, H. Zhao and C. Joe-Wong, Hierarchical Conversational Preference Elicitation with Bandit Feedback, ACM CIKM 2022.

S. Gupta*, J. Zuo*, C. Joe-Wong, G. Joshi and O. Yagan, Correlated Combinatorial Bandits for Online Resource Allocation, ACM MobiHoc 2022. Preliminary version received the Best Poster Award at ACM SIGMETRICS 2022. *Equal contribution

J. Zuo, X. Liu, C. Joe-Wong, J. C. S. Lui and W. Chen, Online Competitive Influence Maximization, AISTATS 2022.

S.S. Azam, T. Kim, S. Hosseinalipour, C. Joe-Wong, S. Bagchi and C. Brinton, Can we Generalize and Distribute Private Representation Learning?, AISTATS 2022.

T. Kim, S. Sathyanarayana, S. Chen, Y. Im, X. Zhang, S. Ha and C. Joe-Wong, MoDEMS: Optimizing Edge Computing for User Mobility, IEEE INFOCOM 2022. Preliminary version appeared as a poster in IEEE IWQoS 2021.

Y. Ruan and C. Joe-Wong, FedSoft: Soft Clustered Federated Learning with Proximal Local Updating, AAAI 2022.

H. Jiang, X. Zhang and C. Joe-Wong, DOLL: Distributed OnLine Learning using Preemptible Cloud Instances, MAMA 2022, held in conjunction with ACM SIGMETRICS/IFIP Performance 2022.

S. Lin, Y. Yao, H. Y. Noh, P. Zhang and C. Joe-Wong, A Neural-Based Bandit Approach to Mobile Crowdsourcing, ACM HotMobile 2022.

T. Kim, S. Singh, N. Madaan and C. Joe-Wong, Grey-Box Defense for Personalized Federated Learning, Best Student Poster Award at CrossFL 2022, held in conjunction with MLSys 2022.

K. Pansetty, Y. Yao, M. Mahdi Kamani and C. Joe-Wong, Personalized Federated Graph Learning, CrossFL 2022, held in conjunction with MLSys 2022.

Y. Yao and C. Joe-Wong, FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks, FedGraph 2022, held in conjunction with ACM CIKM 2022.

Y. Yao, M. Mahdi Kamani, E. Cheng, L. Chen, C. Joe-Wong and T. Liu, FedRule: Federated Rule Recommendation System with Graph Neural Networks, Workshop on Federated Learning: Recent Advances and New Challenges, held in conjunction with NeurIPS 2022.

X. Zhang, J. Wang, L.-F. Lee, T. Yang, A. Kalra, G. Joshi and C. Joe-Wong, Machine Learning on Volatile Instances, IEEE/ACM Transactions on Networking. Preliminary version appeared in IEEE INFOCOM 2020.

G. Lan, Z. Liu, Y. Zhang, T. Scargill, J. Stojkovic, C. Joe-Wong and M Gorlatova, Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality, ACM Transactions on Sensor Networks. Preliminary version appeared in ACM IPSN 2020.

S. Wang, Y. Ruan, Y. Tu, S. Wagle, C. G. Brinton and C. Joe-Wong, Network-Aware Optimization of Distributed Learning for Fog Computing, IEEE/ACM Transactions on Networking. Preliminary version appeared in IEEE INFOCOM 2020.

Y. Fan, Y. Yao and C. Joe-Wong, GCN-SE: Attention as Explainability for Node Classification in Dynamic Graphs, IEEE ICDM 2021 (short paper).

A. F. Baarzi, G. Kesidis, C. Joe-Wong and M. Shahrad, On Merits and Viability of Multi-Cloud Serverless, ACM Symposium on Cloud Computing 2021 (vision paper).

Y. Ruan, X. Zhang and C. Joe-Wong, How Valuable Is Your Data? Optimizing Device Recruitment in Federated Learning, WiOpt 2021.

P. Kortoci, A. Mehrabi, C. Joe-Wong and M. Di Francesco, Incentivizing Opportunistic Data Collection for Time-Sensitive IoT Applications, IEEE SECON 2021.

Y. Ruan, X. Zhang, S.-C. Liang and C. Joe-Wong, Towards Flexible Device Participation in Federated Learning, AISTATS 2021.

Y. Yao and C. Joe-Wong, Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks, AAAI 2021.

J. Zuo and C. Joe-Wong, Combinatorial Multi-armed Bandits for Resource Allocation, IEEE CISS 2021 (invited paper).

M. Harishankar, J. Zuo, S. V. Iyer, P. Tague and C. Joe-Wong, Datanet: Enabling Seamless, Metered and Trusted Internet Connectivity without Subscriptions, IEEE ICC 2021 Workshop Towards Standardized Secured IoT B5G Networking - Artificial Intelligence and Blockchain (invited paper).

T. Kim, S. Chen, Y. Im, X. Zhang, S. Ha and C. Joe-Wong, MoDEMS: Optimizing Edge Computing for User Mobility, IEEE IWQoS 2021 (poster).

Y. Yao, J. Zuo, H. Noh, P. Zhang and C. Joe-Wong, Optimizing Outdoor Data Collection over Dynamic Heterogeneous Sensors, Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology (MMLDT-CSET 2021) (poster).

Y. Ruan, L. Zheng, M. Gorlatova, M. Chiang and C. Joe-Wong, The Economics of Fog Computing: Pricing Tradeoffs for Data Analytics, to appear in Fog and Fogonomics: Challenges and Practices of Fog Computing, Networking, Strategy and Economics, Wiley, 2020.

J. Chung, C. Joe-Wong and S. Ha, Extending the Cloud to Fog: Highly Available Elastic Fog, to appear in Fog and Fogonomics: Challenges and Practices of Fog Computing, Networking, Strategy and Economics, Wiley, 2020.

Y. Jiang, M. Shahrad, D. Wentzlaff, D. H. K. Tsang and C. Joe-Wong, Burstable Instances for Clouds: Performance Modeling, Equilibrium Analysis, and Revenue Maximization, IEEE/ACM Transactions on Networking, 2020. Preliminary version appeared in IEEE INFOCOM 2019.

S. Liu, C. Joe-Wong, J. Chen, C. G. Brinton, C. W. Tan and L. Zheng, Economic Viability of a Virtual ISP, IEEE/ACM Transactions on Networking, 2020. Preliminary version appeared in IEEE INFOCOM 2017.

X. Chen, S. Xu, J. Han, H. Fu, X. Pi, C. Joe-Wong, L. Zhang, H. Noh and P. Zhang, PAS: Prediction Based Actuation System for City-scale Ride Sharing Vehicular Mobile Crowdsensing, IEEE Internet of Things Journal, 2020.

P. Rahimzadeh, J. Lee, Y. Im, S.-C. Mau, E. C. Lee, B. O. Smith, F. Al-Duoli, C. Joe-Wong and S. Ha, SPARCLE: Stream Processing Applications over Dispersed Computing Networks, IEEE ICDCS 2020.

Z. Liu, G. Lan, J. Stojkovic, Y. Zhang, C. Joe-Wong and M. Gorlatova, CollabAR: Edge-assisted Collaborative Image Recognition for Mobile Augmented Reality, ACM IPSN 2020.

K. T. Kim, C. Joe-Wong and M. Chiang, Coded Edge Computing, IEEE INFOCOM 2020.

T. Mohamed, C. Joe-Wong, R. Babbar and M. Di Francesco, Distributed Inference Acceleration with Adaptive DNN Partitioning and Offloading, IEEE INFOCOM 2020.

Y. Ruan and C. Joe-Wong, On the Economic Value of Mobile Caching, IEEE INFOCOM 2020.

Y. Tu, Y. Ruan, S. Wagle, C. G. Brinton and C. Joe-Wong, Network-Aware Optimization of Distributed Learning for Fog Computing, IEEE INFOCOM 2020.

X. Zhang, J. Wang, G. Joshi and C. Joe-Wong, Machine Learning on Volatile Instances, IEEE INFOCOM 2020.

J. Zuo, X. Zhang and C. Joe-Wong, Observe Before Play: Multi-Armed Bandits with Pre-Observations, AAAI 2020.

P. A. Kienscherf, J. Collins,C. Joe-Wong, W. Ketter and S. Sen, Time-Dependent Electricity Pricing Using Variable Announcement Horizons, DACH+ Conference on Energy Informatics 2020.

X. Li, S. Gomena, L. Ballard, J. Li, E. Aryafar and C. Joe-Wong, A Community Platform for Research on Pricing and Distributed Machine Learning, IEEE ICDCS 2020 (demo).

Z. Wu, X. Zhang, S. Xu, X. Chen, P. Zhang, H. Y. Noh and C. Joe-Wong, A Generative Simulation Platform for Multi-agent Systems with Incentives, ACM UbiComp Workshop on Combining Physical and Data-Driven Knowledge in Ubiquitous Computing, 2020.

S. Xu, X. Chen, C. Joe-Wong, P. Zhang and H. Noh, iLoCuS: Incentivizing Vehicle Mobility to Optimize Sensing Distribution in Crowd Sensing, IEEE Transactions on Mobile Computing, 2019.

M. Harishankar, S. Pilaka, P. Sharma, N. Srinivasan, C. Joe-Wong, and P. Tague, Procuring Spontaneous Session-level Resource Guarantees for Real-time Applications: An Auction Approach, IEEE Journal on Selected Areas in Communications, 2019.

S. Sen, C. Joe-Wong, S. Ha and M. Chiang, Time-Dependent Pricing for Multimedia Data Traffic: Analysis, Systems, & Trials, IEEE Journal on Selected Areas in Communications, 2019.

X. Zhang, S. Chen, Y. Im, M. Gorlatova, S. Ha and C. Joe-Wong, Towards Automated Network Management: Learning the Optimal Protocol Selection, IEEE ICNP 2019 (short paper).

E. Aryafar, A. Keshavarz-Haddad and C. Joe-Wong, Proportional Fair RAT Aggregation in HetNets, ITC 31.

P. Rahimzadeh, Y. Im, G. Jung, C. Joe-Wong and S. Ha, ECHO: Efficiently Overbooking Applications to Create a Highly Available Cloud, IEEE ICDCS 2019.

J. Lee, J. Lee, Y. Im, S. Sathyanarayana, P. Rahimzadeh, X. Zhang, M. Hollingsworth, C. Joe-Wong, D. Grunwald and S. Ha, CASTLE over the Air: Distributed Scheduling for Cellular Data Transmissions, ACM MobiSys 2019.

Y. Im, P. Rahimzadeh, B. Shouse, S. Park, C. Joe-Wong, K. Lee and S. Ha, I Sent It: Where Does Slow Data Go to Wait?, ACM EuroSys 2019.

Y. Jiang, M. Shahrad, D. Wentzlaff, D. H. K. Tsang and C. Joe-Wong, Burstable Instances for Clouds: Performance Modeling, Equilibrium Analysis, and Revenue Maximization, IEEE INFOCOM 2019.

P. Kortoci, L. Zheng, C. Joe-Wong, M. Di Francesco and M. Chiang, Fog-based Data Offloading in Urban IoT Scenarios, IEEE INFOCOM 2019.

X. Zhang, S. Chen, Y. Im, M. Gorlatova, S. Ha and C. Joe-Wong, Optimal Learning-based Network Protocol Selection, ACM/IEEE ISCA Workshop on Machine Learning for Systems 2019.

X. Chen, S. Xu, H. Fu, C. Joe-Wong, L. Zhang, H. Y. Noh and P. Zhang, ASC: Actuation System for City-wide Crowdsensing with Ride-sharing Vehicular Platform, Fourth Workshop on International Science of Smart City Operations and Platforms Engineering, co-located with CPS IoT Week 2019.

S. Xu, X. Chen, X. Pi, C. Joe-Wong, P. Zhang and H. Y. Noh, Incentivizing Vehicular Crowdsensing System for Large Scale Smart City Applications, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019.

J. Stojkovic, Z. Liu, G. Lan, C. Joe-Wong and M. Gorlatova, Edge-assisted Collaborative Image Recognition for Augmented Reality, ACM SenSys 2019 (demo).

S. Yerabolu, S. Gomena, E. Aryafar and C. Joe-Wong, An Edge Computing Marketplace for Distributed Machine Learning ACM SIGCOMM 2019 (demo).

S. Sathyanarayana, J. Lee, J. Lee, Y. Im, P. Rahimzadeh, X. Zhang, M. Hollingsworth, C. Joe-Wong, D. Grunwald and S. Ha, Demo: CASTLE over the Air: Distributed Scheduling for Cellular Data Transmissions, ACM MobiSys 2019 (demo).

C. Joe-Wong, L. Zheng and J. Chen, Oligopoly Pricing, Encyclopedia for Wireless Networks, Springer, 2018.

C. Joe-Wong and S. Sen, Harnessing the Power of the Cloud: Revenue, Fairness, and Cloud Neutrality, Journal of Management and Information Systems, 2018.

C. Joe-Wong, S. Sen and S. Ha, Sponsoring Mobile Data: Analyzing the Impact on Internet Stakeholders, IEEE/ACM Transactions on Networking, 2018. Preliminary version appeared in IEEE INFOCOM 2015.

C. Ruiz, S. Pan, A. Bannis, X. Chen, C. Joe-Wong, H. Y. Noh and P. Zhang, IDrone: Robust drone identification through motion actuation feedback, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (formerly ACM UBICOMP), 2018.

W. Chen, C. Joe-Wong, C. G. Brinton, L. Zheng and D. Cao, Principles of Assessing Adaptive Online Courses, Educational Data Mining 2018.

M. Harishankar, N. Srinivasan, C. Joe-Wong and P. Tague, To Accept or Not to Accept: The Question of Supplemental Discount Offers in Mobile Data Plans, IEEE INFOCOM 2018.

M. Khodak, L. Zheng, A. S. Lan, C. Joe-Wong and M. Chiang, Learning Cloud Dynamics to Optimize Spot Instance Bidding Strategies, IEEE INFOCOM 2018.

T. Oda and C. Joe-Wong, MOVI: A Model-Free Approach to Dynamic Fleet Management, IEEE INFOCOM 2018.

T.-Y. Yang, C. G. Brinton and C. Joe-Wong, Predicting Learner Interactions in Social Learning Networks, IEEE INFOCOM 2018.

L. Zheng, C. Joe-Wong, M. Andrews and M. Chiang, Optimizing Data Plans: Usage Dynamics in Mobile Data Networks, IEEE INFOCOM 2018.

M. Harishankar, P. Tague and C. Joe-Wong, Network Slicing as an Ad-Hoc Service: Opportunities and Challenges in Enabling User-Driven Resource Management in 5G, Workshop on Trustworthy & Real-time Edge Computing for Cyber-Physical Systems (TREC4CPS), co-located with IEEE RTSS 2018.

Y. Ruan and C. Joe-Wong, On the Economic Value of Vehicular Caching, ACM SIGMETRICS Work-in-Progress 2018.

J. Zuo, X. Zhang and C. Joe-Wong, Observe before Play: Multi-armed Bandit with Pre-Observations, ACM SIGMETRICS Work-in-Progress 2018.

C. Joe-Wong, L. Zheng, S. Ha, S. Sen, C. W. Tan and M. Chiang, Smart Data Pricing in 5G Systems, Key Technologies for 5G Wireless Systems, Cambridge University Press, 2017.

T.-Y. Yang, C. G. Brinton, C. Joe-Wong and M. Chiang, Behavior-Based Grade Prediction for MOOCs via Time Series Neural Networks, IEEE Journal of Special Topics in Signal Processing, 2017.

K. Shin, C. Joe-Wong, S. Ha, Y. Yi, I. Rhee and D. Reeves, T-Chain: A General Incentive Scheme for Cooperative Computing, IEEE/ACM Transactions on Networking, February 2017. Preliminary version appeared in ICDCS 2015.

L. Zheng, C. Joe-Wong, C. W. Tan, S. Ha and M. Chiang, Customized Data Plans for Mobile Users: Feasibility and Benefits of Data Trading, IEEE Journal of Selected Areas in Communications, May 2017. Preliminary version appeared in IEEE INFOCOM 2015.

L. Zheng, J. Chen, C. Joe-Wong, C. W. Tan and M. Chiang, An Economic Analysis of Wireless Network Infrastructure Sharing, WiOpt 2017.

E. Aryafar, A. Keshavarz-Haddad, C. Joe-Wong and M. Chiang, Max-Min Fair Resource Allocation in HetNets: Distributed Algorithms and Hybrid Architecture, IEEE ICDCS 2017.

Y. Im, J. Han, J. H. Lee, Y. Kwon, C. Joe-Wong, T. Kwon and S. Ha, FLARE: Coordinated Rate Adaptation for HTTP Adaptive Streaming in Cellular Networks, IEEE ICDCS 2017.

Z. Huang, M. Weinberg, L. Zheng, M. Chiang and C. Joe-Wong, Discovering Valuations and Enforcing Truthfulness in a Deadline-Aware Scheduler, IEEE INFOCOM 2017.

P. Rahimzadeh, C. Joe-Wong, K. Shin, Y. Im, J. Lee and S. Ha, SVC-TChain: Incentivizing Good Behavior in Layered P2P Video Streaming, IEEE INFOCOM 2017.

L. Zheng, C. Joe-Wong, J. Chen, C. G. Brinton, C. W. Tan and M. Chiang, Economic Viability of a Virtual ISP, IEEE INFOCOM 2017.

A. Jauhri, C. Joe-Wong and J. P. Shen, On the Real-Time Vehicle Placement Problem, NIPS Workshop on Machine Learning for Intelligent Transportation Systems 2017.

C. Joe-Wong, S. Ha, Z. Liu, F. M. F. Wong and M. Chiang, Mind Your Own Bandwidth, Fog for 5G and IoT, Wiley, 2016. Preliminary version appeared in IEEE/ACM IWQoS 2015.

Y. Im, C. Joe-Wong, S. Ha, S. Sen, T. Kwon, and M. Chiang, AMUSE: Empowering Users for Cost-Aware Offloading with Throughput-Delay Tradeoffs, IEEE Transactions on Mobile Computing, May 2016. Preliminary version appeared in IEEE INFOCOM 2013 (mini-conference).

C. Joe-Wong, Y. Im, K. Shin and S. Ha, A Performance Analysis of Incentive Mechanisms for Cooperative Computing, IEEE ICDCS 2016.

L. Zheng, C. Joe-Wong, C. Brinton, C. W. Tan, S. Ha and M. Chiang, On the Viability of a Cloud Virtual Service Provider, ACM SIGMETRICS 2016.

S. Sen, C. Joe-Wong, S. Ha and M. Chiang, Time-Dependent Pricing in Mobile Data Plans: Results from a Field Deployment in Alaska, WITS 2016.

Y. Wang, C. Joe-Wong and S. Sen, Congestion Externalities, Content Exclusivity, and Internet Fragmentation, WITS (Workshop on Internet Technologies and Systems) 2016 (poster).

L. Zheng and C. Joe-Wong, Understanding Rollover Data, Smart Data Pricing Workshop 2016.