Jie Lu

Orcid: 0000-0002-6831-7413

Affiliations:
  • National Digital Switching System Engineering and Technological Research and Development Center, Zhengzhou, China
  • Information Engineering University, Zhengzhou, China
  • Zhejiang University, China (former)


According to our database1, Jie Lu authored at least 14 papers between 2019 and 2024.

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

Timeline

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Bibliography

2024
SuperGuardian: Superspreader removal for cardinality estimation in data streaming.
Inf. Syst., 2024

HeavySeparation: A Generic framework for stream processing faster and more accurate.
Comput. Commun., 2024

2023
Virtual self-adaptive bitmap for online cardinality estimation.
Inf. Syst., March, 2023

2022
SDN-ESRC: A Secure and Resilient Control Plane for Software-Defined Networks.
IEEE Trans. Netw. Serv. Manag., 2022

Filter-Sketch: A two-layer sketch for entropy estimation in the data plane.
IET Commun., 2022

Front Cover: Filter-Sketch: A two-layer sketch for entropy estimation in the data plane.
IET Commun., 2022

Controller robust placement with dynamic traffic in software-defined networking.
Comput. Commun., 2022

P4Resilience: Scalable Resilience for Multi-failure Recovery in SDN with Programmable Data Plane.
Comput. Networks, 2022

LUSketch: A Fast and Precise Sketch for top-k Finding in Data Streams.
Proceedings of the 31st International Conference on Computer Communications and Networks, 2022

MCSketch: An Accurate Sketch for Heavy Flow Detection and Heavy Flow Frequency Estimation.
Proceedings of the Web and Big Data - 6th International Joint Conference, 2022

2021
OrderSketch: An Unbiased and Fast Sketch for Frequency Estimation of Data Streams.
Comput. Networks, 2021

2019
SGS: Safe-Guard Scheme for Protecting Control Plane Against DDoS Attacks in Software-Defined Networking.
IEEE Access, 2019

A Survey of Controller Placement Problem in Software-Defined Networking.
IEEE Access, 2019

Elastic Virtual Network Function Orchestration Policy Based on Workload Prediction.
IEEE Access, 2019


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