Zhi-Li Zhang

First name
Zhi-Li
Last name
Zhang
Dayalan, U. K., Wu, Z., Gautam, G., Tian, F., & Zhang, Z.-L. (2023). Towards an eBPF+XDP Based Framework for Open, Programmable and Scalable NextG RANs. In (p. 6). IEEE. http://doi.org/10.1109/FNWF58287.2023.10520475
Dayalan, U. K., Salo, T. J., Fezeu, R. K., & Zhang, Z.-L. (2023). Kaala 2.0: Scalable IoT/NextG System Simulator. IEEE Network, 37(3), 7. http://doi.org/10.1109/MNET.002.2200498
Ye, W., Hu, X., Liu, T., Sun, R., Li, Y., & Zhang, Z.-L. (2022). 5GNN: extrapolating 5G measurements through GNNs. In Proceedings of the 1st International Workshop on Graph Neural Networking (GNNet ’22: ) (p. 6). http://doi.org/10.1145/3565473.3569186
Wu, Z., Zhang, Y., Feng, W., & Zhang, Z.-L. (2022). NFlow and MVT Abstractions for NFV Scaling. In IEEE INFOCOM 2022 (p. 10). http://doi.org/10.1109/INFOCOM48880.2022.9796764
Ramadan, E., Mekky, H., Jin, C. J., Dumba, B., & Zhang, Z.-L. (2021). Taproot: Resilient Diversity Routing with Bounded Latency. In ACM SIGCOMM Symposium on SDN Research (SOSR). http://doi.org/10.1145/3482898.3483364
Tian, F., Zhang, Y., Ye, W., Jin, C., Wu, Z., & Zhang, Z.-L. (2021). Accelerating Distributed Deep Learning using Multi-Path RDMA in Data Center Networks. In ACM SIGCOMM Symposium on Software Defined Networking Research (SOSR’21). http://doi.org/10.1145/3482898.3483363
Ramadan, E., Narayanan, A., Dayalan, U. K., Fezeu, R. A., Qian, F., & Zhang, Z.-L. (2021). Case for 5G-aware video streaming applications. In 5G-MeMU ’21: Proceedings of the 1st Workshop on 5G Measurements, Modeling, and Use Cases (p. 8). http://doi.org/10.1145/3472771.3474036
Zhang, Z.-L., Dayalan, U. K., Ramadan, E., & Salo, T. J. (2021). Towards a Software-Defined, Fine-Grained QoS Framework for 5G and Beyond Networks. In NAI’21: Proceedings of the ACM SIGCOMM 2021 Workshop on Network-Application Integration (p. 7). http://doi.org/10.1145/3472727.3472798
Rathee, S., Varyani, N., Haribabu, K., Bajaj, A., Bhatia, A., Jashnani, R., & Zhang, Z.-L. (2021). GlobeSnap: An Efficient Globally Consistent Statistics Collection for Software-Defined Networks. Journal of Network and Systems Management, 29(3). http://doi.org/10.1007/s10922-021-09601-z
Narayanan, A., Ramadan, E., Mehta, R., Hu, X., Liu, Q., Fezeu, R. A., … Zhang, Z.-L. (2020). Lumos5G: Mapping and Predicting Commercial mmWave 5G Throughput. In ACM IMC 2020 (p. 18). http://doi.org/10.1145/3419394.3423629