Xiaolin Duan

dblp:76/7882 · DBLP profile ↗
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14ranked-venue papers
1as first author
12since 2021 · last 2026
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 7 · 7 since 2021Computer networks · 4 · 3 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 since 2021Security and privacy · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2026 A Novel Leakage Model in OpenSSL's Miller-Rabin Primality Test
Xiaolin Duan, Honggang Hu
PKC (4)1
2026 Cost-aware scheduling for streaming applications in geographically distributed heterogeneous cloud
Lisha Zhu, Xiaolin Duan
Future Gener. Comput. Syst.4
2026 Cost-efficient and topology-aware scheduling algorithms in distributed stream computing systems
Shuheng Wang, Gangfan Tan, Xiaolin Duan
Future Gener. Comput. Syst.4
2026 A Three-tier Load Balancing Model with Dynamic Data Partitioning Strategy for Distributed Stream Processing
Yifan Ren, Xiaolin Duan
J. Grid Comput.4
2026 Profit maximization for cloud-edge-end collaborative offloading via Chaotic-Optimized Spider Wasp Optimizer algorithm
Jiutong Liu, Xiaolin Duan, Liangjie Liu
J. Netw. Comput. Appl.3
2025 A UAV-assisted dynamic offloading based on maximum clique algorithm with weighted graphs in mobile edge computing
Xiaolin Duan, Jiutong Liu
Comput. Networks5
2025 Energy-aware scheduling and two-tier coordinated load balancing for streaming applications in apache flink
Xiaolin Duan, Jianglin Xia
Future Gener. Comput. Syst.3
2025 Cost-effective container elastic scaling and scheduling under multi-resource constraints
Yuzheng Cui, Xiaolin Duan
J. Netw. Comput. Appl.4
2025 Adaptive scheduling framework of streaming applications based on performance-to-cost ratio in heterogeneous cloud environment
Gangfan Tan, Chenzi Wang, Xiaolin Duan
J. Supercomput.6
2024 SLA-based task offloading for energy consumption constrained workflows in fog computing
Xiaolin Duan
Future Gener. Comput. Syst.4
2024 Adaptive Scheduling Framework of Streaming Applications based on Resource Demand Prediction with Hybrid Algorithms
Wenbin Xie, Huaqing Ye, Xiaolin Duan
J. Grid Comput.5
2021 Attention cutting and padding learning for fine-grained image recognition
Xiaolin Duan, Xiangyan Zeng, Mingxuan He
Multim. Tools Appl.3
2020 Hierarchical saliency mapping for weakly supervised object localization based on class activation mapping
Xiangyan Zeng, Xiaolin Duan
Multim. Tools Appl.5
2009 VB-Rescheduling: An Efficient Data Channel Rescheduling Algorithm Based on Virtual Burst for OBS Networks
abstract
In optical burst switching (OBS) networks, the data channel scheduling algorithm is one of the most important issues, which have a great impact on network performances. Currently, there are various data channel scheduling algorithms. Among them, the rescheduling algorithm is more attractive because it could adaptively reallocate the data channels even when they have been occupied by some data bursts (DB), and release some channel resource for the latter DB in most situations. However when the traffic load is heavy, it is not effective any more, and would worsen network performance. Therefore, this paper proposes a new rescheduling algorithm, namely VB-Rescheduling algorithm. According to the state of the data channels, it reschedules data blocks on demand by three granularities (i.e., virtual burst, child-burst cluster and normal burst). Compared with other rescheduling algorithms, it has some advantages as follows. Firstly, it could keep the same sequence of the arriving data bursts at a node as the corresponding control packets. Secondly, it is more flexible to reschedule data blocks. Finally, simulation results show that it can greatly improve OBS network performance in terms of the overall packet loss probability and the link utilization, compared with traditional OBS rescheduling algorithm (whose rescheduling granularity is normal burst) and the native virtual burst scheduling scheme.
Keping Long, Fenfen Dong, Sheng Huang 0001, Xiaolin Duan
ICC6