Publications

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Journal Articles

[J1] Sampling-Based Multi-Job Placement for Heterogeneous Deep Learning Clusters

Published in IEEE Transactions on Parallel and Distributed Systems, 2024

This paper is about multi-job placement to accelerate distributed deep learning in data center networks.

Recommended citation: Kaiyang Liu, Jingrong Wang, Zhiming Huang, Jianping Pan, Sampling-based multi-job placement for heterogeneous deep learning clusters, IEEE Transactions on Parallel and Distributed Systems, vol. 35, no. 6, pp. 874–888, 2024.
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[J2] Sampling-Based Caching for Low Latency in Distributed Coded Storage Systems

Published in IEEE Transactions on Services Computing, 2023

This paper is about a sampling-based cache content replacement scheme in geo-distributed cloud/edge networks.

Recommended citation: Kaiyang Liu, Jingrong Wang, Heng Li, Jun Peng, Jianping Pan, Sampling-based caching for low latency in distributed coded storage systems, IEEE Transactions on Services Computing, vol. 16, no. 6, pp. 4275–4287, 2023.
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[J3] Adaptive and Scalable Caching With Erasure Codes in Distributed Cloud-Edge Storage Systems

Published in IEEE Transactions on Cloud Computing, 2023

This paper is about adaptive cache content replacement scheme in geo-distributed cloud/edge networks.

Recommended citation: Kaiyang Liu, Jun Peng, Jingrong Wang, Zhiwu Huang, Jianping Pan, Adaptive and scalable caching for low latency in distributed coded storage systems, IEEE Transactions on Cloud Computing, vol. 11, no. 2, pp. 1840–1853, 2023.
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[J4] Optimal Caching for Low Latency in Distributed Coded Storage Systems

Published in IEEE/ACM Transactions on Networking, 2022

This paper is about an optimal cache content replacement scheme in geo-distributed cloud/edge networks.

Recommended citation: Kaiyang Liu, Jun Peng, Jingrong Wang, Jianping Pan, Optimal caching for low latency in distributed coded storage systems, IEEE/ACM Transactions on Networking, vol. 30, no. 3, pp. 1132–1145, 2022.
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[J6] A Learning-Based Data Placement Framework for Low Latency in Data Center Networks

Published in IEEE Transactions on Cloud Computing, 2022

This paper is about learning-based data placement for intra-data center networks.

Recommended citation: Kaiyang Liu, Jun Peng, Jingrong Wang, Boyang Yu, Zhuofan Liao, Zhiwu Huang, Jianping Pan. A learning-based data placement framework for low latency in data center networks, IEEE Transactions on Cloud Computing, vol. 10, no. 1, pp. 146–157, 2022.
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[J7] An Instance Reservation Framework for Cost Effective Services in Geo-Distributed Data Centers

Published in IEEE Transactions on Services Computing, 2021

This paper is about flexible computation resource reservation and task placement in geo-distributed data centers.

Recommended citation: Kaiyang Liu, Jun Peng, Boyang Yu, Weirong Liu, Zhiwu Huang, Jianping Pan. An instance reservation framework for cost effective services in geo-distributed data centers, IEEE Transactions on Services Computing, vol. 14, no. 2, pp. 356–370, 2021.
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[J11] Scalable and Adaptive Data Replica Placement for Geo-Distributed Cloud Storages

Published in IEEE Transactions on Parallel and Distributed Systems, 2020

This paper is about community discovery and adjustment based data replica placement schemes in geo-distributed cloud storage systems.

Recommended citation: Kaiyang Liu, Jun Peng, Jingrong Wang, Weirong Liu, Zhiwu Huang, Jianping Pan. Scalable and adaptive data replica placement for geo-distributed cloud storages, IEEE Transactions on Parallel and Distributed Systems, vol. 31, no. 7, pp. 1575–1587, 2020.
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Conference Papers

[C2] End-to-End Congestion Control as Learning for Unknown Games with Bandit Feedback

Published in IEEE 43rd International Conference on Distributed Computing Systems (ICDCS), 2023

This paper is about learning-based congestion control for computer networks.

Recommended citation: Zhiming Huang, Kaiyang Liu, Jianping Pan. End-to-end congestion control as learning for unknown games with Bandit feedback, IEEE International Conference on Distributed Computing Systems, 2023.
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[C5] Learning-based Adaptive Data Placement for Low Latency in Data Center Networks

Published in IEEE Conference on Local Computer Networks (LCN), 2018

This paper is about learning-based data placement for intra-data center networks.

Recommended citation: Kaiyang Liu, Jingrong Wang, Zhuofan Liao, Boyang Yu, Jianping Pan. Learning-based adaptive data placement for low latency in data center networks, IEEE Conference on Local Computer Networks, pp. 142–149, 2018.
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