Cited by 74Software-Defined Networks and 5GCloud Computing and Resource ManagementAdvanced Optical Network Technologies

MDP and Machine Learning-Based Cost-Optimization of Dynamic Resource Allocation for Network Function Virtualization

Shi, Runyu, Zhang, Jia, Chu, Wenjing, Bao, Qihao, Jin, Xiatao, Gong, Chenran, Zhu, Qihao, Yu, Chang +1 more·2015·2015 IEEE International Conference on Services Computing

Abstract

The introduction of Network Functions Virtualization (NFV) enables service providers to offer software-defined network functions with elasticity and flexibility. Its core technique, dynamic allocation procedure of NFV components onto cloud resources requires rapid response to changes on-demand to remain cost and QoS effective. In this paper, Markov Decision Process (MDP) is applied to the NP-hard problem to dynamically allocate cloud resources for NFV components. In addition, Bayesian learning method is applied to monitor the historical resource usage in order to predict future resource reliability. Experimental results show that our proposed strategy outperforms related approaches.

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Crossref · 10.1109/scc.2015.19

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37 of 37 references verified0 citation errors · 0 not checkable

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Authors
Shi, R., Zhang, J., Chu, W., Bao, Q., Jin, X., Gong, C., Zhu, Q., Yu, C., & Rosenberg, S.
Affiliations
  • DELL (United States) (US)
  • Carnegie Mellon University (US)
Venue
2015 IEEE International Conference on Services Computing
Publisher
IEEE
Published
2015-06
Pages
65-73
OpenAlex
W1525264275
Cited by
74
References
37
Citations by year
2026: 1 · 2025: 2 · 2024: 6 · 2023: 8 · 2022: 3 · 2021: 13 · 2020: 14 · 2019: 12 · 2018: 8 · 2017: 5 · 2016: 2
FWCI
3.72
Type
conference paper
Language
en
Open access
closed
Locations
IEEE International Conference on Services Computing (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Optical Network Technologies
Keywords
network function virtualization, dynamic resource allocation, cloud resource allocation, cost optimization, Markov decision process, Bayesian learning, resource usage prediction, software-defined networking, quality of service

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