Research on Optimization of Service Function Chain Path Based on Graph Attention Network

HUANG Wanwei; LI Song; ZHANG Chaoqin; WANG Sunan; ZHANG Xiaohui

doi:10.11999/JEIT210458

Volume 44 Issue 8

Aug. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(8): 2833-2841

HUANG Wanwei, LI Song, ZHANG Chaoqin, WANG Sunan, ZHANG Xiaohui. Research on Optimization of Service Function Chain Path Based on Graph Attention Network[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2833-2841. doi: 10.11999/JEIT210458

Citation:

HUANG Wanwei, LI Song, ZHANG Chaoqin, WANG Sunan, ZHANG Xiaohui. Research on Optimization of Service Function Chain Path Based on Graph Attention Network[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2833-2841. doi: 10.11999/JEIT210458

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Research on Optimization of Service Function Chain Path Based on Graph Attention Network

doi: 10.11999/JEIT210458

1.
College of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
2.
College of Computer and Commucation Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China
3.
School of Electronic and Communication Engineering Shenzhen Polytechnic, Shenzhen 518005, China
4.
Henan Xin’an Communication Technology Co. Ltd, Zhengzhou 450000, China

Funds: The National Natural Science Foundation of China (62072416, 62072414)

Received Date: 2021-05-25
Rev Recd Date: 2021-10-26

Available Online: 2021-11-19

Publish Date: 2022-08-17

Abstract

Abstract

Service Function Chain (SFC) path generation aims to provide users with diversified network function customization services with high speed and low delay. Most of the existing SFC path selection algorithms aim at specific network topology or use a single evaluation index, which has the problems of weak generalization and single evaluation standard. In view of this, an SFC path selection optimization model (SFC-GAT) based on Graph ATtention network (GAT) is proposed. Its core is no longer to fix the network topology, but to model the SFC path selection problem as a path attention problem. The generalization of the model is enhanced by redesigning the path selection diagram and path update strategy; The effect of path optimization from the perspective of delay and load capacity is evaluated to solve the problem of single evaluation of path performance. The simulation results show that compared with the shortest path and minimum overload path selection strategy under constraints, SFC-GAT can improve the comprehensive performance of path selection by at least 12% and 7%.
- Service Function Chain(SFC),
- Graph ATtention network(GAT),
- Attention mechanism,
- Path selection

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References(15)

References

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