Yin Li

Affiliations:
  • Guangzhou Institute of Software Application Technology, China
  • Chinese Academy of Sciences, Institute of Software, Beijing, China (PhD 2010)


According to our database1, Yin Li authored at least 10 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
A Performance and Reliability-Guaranteed Predictive Approach to Service Migration Path Selection in Mobile Computing.
IEEE Internet Things J., October, 2023

A Multi-Armed Bandits Learning-Based Approach to Service Caching in Edge Computing Environment.
Proceedings of the Web Services - ICWS 2023, 2023

DQN-Based Applications Offloading with Multiple Interdependent Tasks in Mobile Edge Computing.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2023

A Novel Deep Federated Learning-Based and Profit-Driven Service Caching Method.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2023

M-MNFT: A Novel Modified (m, n)-Fault Tolerance Approach for Service Migration in Vehicular Edge Computing.
Proceedings of the IEEE International Conference on Software Services Engineering, 2023

2022
A Novel Approach for User Demand-aware Data Center Construction and Service Consolidation.
Proceedings of the Web Services - ICWS 2022, 2022

A Method for Mobile-Aware Multi-Vehicular Offloading in Hybrid Cloud-Edge Environment.
Proceedings of the 24th IEEE Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, 2022

2021
A Novel Approach to Taxi-GPS-Trace-Aware Bus Network Planning.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2021

2020
Location-Aware Edge Service Migration for Mobile User Reallocation in Crowded Scenes.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2020

Reactive Workflow Scheduling in Fluctuant Infrastructure-as-a-Service Clouds Using Deep Reinforcement Learning.
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2020


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