Research Article
BPA: The Optimal Placement of Interdependent VNFs in Many-Core System
@INPROCEEDINGS{10.1007/978-3-030-67540-0_18, author={Youbing Zhong and Zhou Zhou and Xuan Liu and Da Li and Meijun Guo and Shuai Zhang and Qingyun Liu and Li Guo}, title={BPA: The Optimal Placement of Interdependent VNFs in Many-Core System}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16--18, 2020, Proceedings, Part II}, proceedings_a={COLLABORATECOM PART 2}, year={2021}, month={1}, keywords={NFV SFCs plaecment Interdependent NFs NUMA}, doi={10.1007/978-3-030-67540-0_18} }- Youbing Zhong
Zhou Zhou
Xuan Liu
Da Li
Meijun Guo
Shuai Zhang
Qingyun Liu
Li Guo
Year: 2021
BPA: The Optimal Placement of Interdependent VNFs in Many-Core System
COLLABORATECOM PART 2
Springer
DOI: 10.1007/978-3-030-67540-0_18
Abstract
Network function virtualization (NFV) brings the potential to provide the flexible implementation of network functions and reduce overall hardware cost by running service function chains (SFCs) on commercial off-the-shelf servers with many-core processors. Towards this direction, both academia and industry have spent vast amounts of effort to address the optimal placement challenges of NFV middleboxes. Most of the servers usually are equipped with Intel X86 processors, which adopt Non-Uniform Memory Access (NUMA) architecture. However, existing solutions for placing SFCs in one server either ignore the impact of hardware architecture or overlook the dependency between middleboxes. Our empirical analysis shows that the placement of virtual network functions (VNFs) with interdependency in a server needs more particular consideration. In this paper, we first manage the optimal placement of VNFs by jointly considering the discrepancy of cores in different NUMA nodes and interdependency between network functions (NFs), and formulate the optimization problem as a Non-Linear Integer Programming (NLIP) model. Then we find a reasonable metric to describe the dependency relation formally. Finally, we propose a heuristic-based backtracking placement algorithm (BPA) to find the near-optimal placement solution. The evaluation shows that, compared with two state-of-art placement strategies, our algorithm can improve the aggregate performance by an average of 20% or 45% within an acceptable time range.
