RuleDRL: Reliability-Aware SFC Provisioning With Bounded Approximations in Dynamic Environments-Reference-Cited by-同舟云学术

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RuleDRL: Reliability-Aware SFC Provisioning With Bounded Approximations in Dynamic Environments

Published:2023-09 Issue:5 Volume:16 Page:3651-3664
ISSN:1939-1374
Container-title:IEEE Transactions on Services Computing
language:
Short-container-title:IEEE Trans. Serv. Comput.

Author:

Zeng Yue¹^ORCID,Qu Zhihao²^ORCID,Guo Song³^ORCID,Tang Bin²^ORCID,Ye Baoliu¹^ORCID,Li Jing³^ORCID,Zhang Jie³^ORCID

Affiliation:

1. Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

2. Key Laboratory of Water Big Data Technology of Ministry of Water Resources, Hohai University, Nanjing, China

3. Department of Computing, The HongKong Polytechnic University, Hung Hom, Hong Kong

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province, China

Future Network Scientific Research Fund

Collaborative Innovation Center of Novel Software Technology and Industrialization

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/4629386/10274114/10138914.pdf?arnumber=10138914

Reference55 articles.

1. Reducing the Service Function Chain Backup Cost over the Edge and Cloud by a Self-adapting Scheme

2. Reducing the Service Function Chain Backup Cost over the Edge and Cloud by a Self-adapting Scheme

3. Towards Fine-grained Resource Allocation in NFV Infrastructures

5. Downtime statistics of current cloud solutions;cérin,2014

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-objective optimization of SFC deployment using service aggregation and computing offload;Computer Communications;2024-08

2. Towards learning-based energy-efficient online coordinated virtual network embedding framework;Computer Networks;2024-02

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