Publications

Optimized Resource Allocation

1. F. Zafari, K.K. Leung, D. Towsley, P. Basu , A. Swami and J. Li, “Let's Share: A Game-Theoretic Framework for Resource Sharing in Mobile Edge Clouds,” submitted to IEEE Transactions on Network and Service Management.
2. F. Zafari, P. Basu, K.K. Leung, J. Li, A. Swami, and D. Towsley, “Resource Sharing in the Edge: A Distributed Bargaining-Theoretic Approach,” submitted to IEEE ICDCS 2020.
3. F. Zafari, K.K. Leung, D. Towsley, P. Basu and A. Swami, “A Game-Theoretic Framework for Resource Sharing in Clouds,” presented at the IEEE/IFIP WMNC, Paris, France, September 2019.
4. F. Zafari, A. Gkelias, and K.K. Leung, “A Survey of Indoor Localization Systems and Technologies,” IEEE Transactions on Control of Network Systems, Early Access 2019.
5. F. Zafari, J. Li, K.K. Leung, D. Towsley, and A. Swami, “Optimal Energy Consumption for Communication, Computation, Caching and Quality Guarantee,” presented at the IEEE/IFIP WMNC, Paris, France, September 2019.
6. N.K. Panigrahy, J. Li, F. Zafari, D. Towsley, and P. Yu, “Jointly Caching and Compressing Data in Wireless Sensor Networks,” presented at the IEEE SMARTCOMP, Washington D.C., June 2019.
7. F. Zafari, J. Li, K.K. Leung, D. Towsley, and A. Swami, “Optimal Energy Tradeoff among Communication, Computation, Caching with QoI Guarantee,” presented at the IEEE Globecom, Abu Dhabi, UAE, December 2018.
8. F. Zafari, J. Li, K.K. Leung, D. Towsley, and A. Swami, “Optimal Energy Tradeoff among Communication, Computation, Caching with QoI Guarantee,” presented at the IEEE Globecom, Abu Dhabi, UAE, December 2018.
9. F. Zafari, J. Li, K.K. Leung, D. Towsley, and A. Swami, “ A Game-Theoretic Approach to Multi-Objective Resource Sharing and Allocation in Mobile Edge ,” presented at the ACM Mobicom, New Delhi, India, October 2018.
10. J. Li, F. Zafari, D. Towsley, K.K. Leung, and A. Swami, “Joint Data Compression and Caching: Approaching Optimality with Guarantees ,” presented at the ACM ICPE, Berlin, Germany, April 2018.

Distributed Machine Learning

1. T. Tuor, S. Wang, K.K. Leung and B.J. Ko, “Online Collection and Forecasting of Resource Utilization in Large-Scale Distributed Systems,” presented at the IEEE ICDCS, Texas, USA, July 2019.
2. S. Wang, T. Tuor, T. Salonidis, K.K. Leung, C. Makaya, T. He and K. Chan, “Adaptive Federated Learning in Resource Constrained Edge Computing Systems,” IEEE Journal on Selected Areas of Communications, Vol. 37, No. 6, pp. 1205-1221, 2019.
3. D. Conway-Jones, T. Tuor, S. Wang and K.K. Leung, “Demonstration of Federated Learning in a Resource-Constrained Networked Environment,” IEEE Smart Computing (SMARTCOMP), Washington D.C., USA, June 2019.
4. T. Tuor, S. Wang and K.K. Leung, “Distributed Machine Learning in Coalition Environments,” 21st International Conference on Information Fusion (Fusion), Cambridge, UK, July 2018.
5. T. Tuor, S. Wang, K.K. Leung and B.J. Ko, “Understanding information leakage of distributed inference with deep nerual networks,” SPIE Commercial + Scientific Sensing and Image Conference, April 2018, Florida, USA.
6. T. Tuor, S. Wang, T. Salonidis,B .J.Ko, K.K. Leung, “ Demo Abstract: Distributed Machine Learning at Resource-Limited Edge Nodes,” presented at the IEEE Infocom, April 2018, Hawaii, USA.
7. S. Wang, T. Tuor, T. Salonidis, K.K. Leung, C. Makaya, T. He and K. Chan, “When Edge Meets Learning: Adaptive control for resource-constrained distributed machine learning,” presented at the IEEE Infocom, April 2018, Hawaii, USA.

SDN Synchronization

1. Z. Zhang, L. Ma, K.K. Leung, K Poularakis, L. Tassiulas, J. Tucker and A. Swami, “Controller Synchronization by Multi-Agent Reinforcement Learning and Temporal Data Enhancement for Distributed SDN,” submitted to IEEE ICDCS 2020.
2. Z. Zhang, L. Ma, K Poularakis, K.K. Leung, J. Tucker and A. Swami, “MACS: Deep Reinforcement Learning based SDN Controller Synchronization Policy Design,” IEEE ICNP, Illinois, USA, October 2019.
3. Z. Zhang, L. Ma, K.K. Leung, F. Le, S. Kompella and L. Tassiulas, “How Advantageous Is It? An Analytical Study of Controller-Assisted Path Construction in Distributed SDN,” IEEE/ACM Transactions on Networking, Vol. 27, No. 4, pp. 1643-1656, July 2019
4. Z. Zhang, L. Ma, K. Poularaki, K.K. Leung and L. Wu, “DQ Scheduler: Deep Reinforcement Learning Based Controller Synchronization in Distributed SDN,” presented at IEEE ICC 2019, Shanghai, China, May 2019 (Best Paper Award).
5. Z. Zhang, L. Ma, K.K. Leung, L. Tassiulas, and J. Tucker, “Q-Placement: Reinforcement-Learning-Based Service Placement in Software-Defined Networks,” presented at the 38th IEEE International Conference on Distributed Computing Systems (ICDCS 2018), Vienna, Austria, July 2018.
6. L. Ma, Z. Zhang, B.J. Ko, M. Srivatsa, and K.K. Leung, “Resource management in distributed SDN using reinforcement learning,” SPIE Commercial + Scientific Sensing and Image Conference, April 2018, Florida, USA.
7. Z. Zhang, L. Ma, K.K. Leung, F.Le, “More Is Not Always Better: An Analytical Study of Controller Synchronizations in Distributed SDN,” Submitted to IEEE/ACM Transactions on Networking.