A novel multimodal deep learning framework for encrypted traffic classification

P Lin, K Ye, Y Hu, Y Lin, CZ Xu - IEEE/ACM Transactions on …, 2022 - ieeexplore.ieee.org
Traffic classification is essential for cybersecurity maintenance and network management,
and has been widely used in QoS (Quality of Service) guarantees, intrusion detection, and …

Flow optimization strategies in data center networks: A survey

Y Liu, T Yu, Q Meng, Q Liu - Journal of Network and Computer Applications, 2024 - Elsevier
In the era of digitization, Data Center Networks (DCN) have emerged as a critical component
supporting infrastructure for cloud computing, big data analytics, online services, and more …

Instant queue occupancy used for automatic traffic scheduling in data center networks

MS Iqbal, C Chen - Computer Networks, 2024 - Elsevier
Datacenter applications desire low latency for short messages to provide a better user
experience. Therefore, one of the goals of datacenter networks is to minimize flow …

Load balancing with deadline-driven parallel data transmission in data center networks

T Zhang, R Huang, Y Hu, Y Li, S Zou… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
With the explosive growth of the Internet of Things (IoT), an increasing amount of sensor
data generated by soft real-time IoT applications has been moved to data centers for storage …

HG: Leveraging Hybrid Switching Granularity to Balance Heterogeneous Data Center Traffic Load for Cloud-Based Industrial Applications

T Zhang, S He, X Zeng, X Wu, K Jin… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Nowadays, the deluge of heterogeneous data generated by various cloud-based industrial
applications often has to be delivered to the data center for analysis and storage. To speed …

A multipath scheduler based on cross-layer information for low-delay applications in 5G edge networks

B Zhao, W Yang, W Du, Y Ren, J Sun, Q Wu, X Zhou - Computer Networks, 2024 - Elsevier
Virtual Reality (VR) applications that require extremely low delay and high image quality are
widely used in online games and other 5G scenarios, becoming a hot research field in …

GraphGRU: A graph neural network model for resource prediction in microservice cluster

H He, L Su, K Ye - 2022 IEEE 28th International Conference on …, 2023 - ieeexplore.ieee.org
Predicting resource usage of workloads in large scale production clusters is very important
to understand the characteristics of applications. It is also very important for cluster operators …

Deep Reinforcement Learning Based Dynamic Flowlet Switching for DCN

X Diao, H Gu, W Wei, G Jiang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Flowlet switching has been proven to be an effective technology for fine-grained load
balancing in data center networks. However, flowlet detection based on static flowlet timeout …

Key Flow First Prioritized Flow Scheduling Strategy In Multi-Tenant Data Centers

X Tao, X Qian, L Han, W Fan, Y Shi… - … on Network and …, 2024 - ieeexplore.ieee.org
The mixed flow in multi-tenant data centers presents a challenge for priority flow scheduling
due to the coexistence of various requirements such as latency and throughput. To address …

Towards Dynamic Request Updating with Elastic Scheduling for Multi-tenant Cloud-based Data Center Network

S Lu, J Wu, J Shi, J Fang, J Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Serving the ever-growing demand for computation, storage, and networking resources for
multi-tenant in cloud computing is an important mission of Data Center Networks (DCNs). In …