TY - JOUR
T1 - Resource-Ability Assisted Service Function Chain Embedding and Scheduling for 6G Networks with Virtualization
AU - Cao, Haotong
AU - Du, Jianbo
AU - Zhao, Haitao
AU - Luo, Daniel Xiapu
AU - Kumar, Neeraj
AU - Yang, Longxiang
AU - Yu, F. Richard
N1 - Funding Information:
Manuscript received September 15, 2020; revised January 27, 2021; accepted March 2, 2021. Date of publication March 17, 2021; date of current version April 22, 2021. This work was supported in part by National Natural Science Foundation of China under Grants 62071246, 61901367, 61427801, and 61372124, in part by National Key Research and Development Program of China under Grant 2018YFC1314903, and in part by Natural Science Foundation of Shanxi Province under Grant 2020JQ-844. The review of this paper was coordinated by Dr. T. De Cola. (Corresponding authors: Daniel Xiapu Luo; Longxiang Yang.) Haotong Cao is with the Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, China, and also with the Department of Computing, The Hong Kong Polytechnic University, Hong Kong SAR, China (e-mail: [email protected]).
Publisher Copyright:
© 1967-2012 IEEE.
PY - 2021/4
Y1 - 2021/4
N2 - While 5G is being deployed all around the world, the industry and academia start the investigation of 6G. Network function virtualization (NFV) is seen as the key enabler towards the flexible resource management and sharing of 6G networks. The main idea of NFV is to decouple the physical devices from the specific functions that run on them. In NFV, virtual network service (NS) is modeled as a service function chain (SFC). The challenges in SFC description, composition, embedding, and scheduling are key issues in NFV. In this paper, we focus on the joint SFC embedding and scheduling for NFV in 6G networks. With the assistance of sensing the physical node resource abilities, we propose a novel SFC embedding and scheduling algorithm, which is named as RA-SFC-6G. A new service is first composed as an SFC which is an ordered sequence of virtual network functions (VNFs). Afterwards, our RA-SFC-6G algorithm will select the physical nodes with stronger resource abilities and abundant resources to accommodate the SFC. In addition, the NS is guaranteed to be implemented without violating the NS maximum allowed scheduling time. If violated, our RA-SFC-6G can re-embed and re-schedule the violated VNFs to suitable positions. In order to validate our RA-SFC-6G performance, we do the experiment work. Experiment results show that our RA-SFC-6G achieves at least 10% higher SFC acceptance ratio than the previous counterparts and the typical heuristics.
AB - While 5G is being deployed all around the world, the industry and academia start the investigation of 6G. Network function virtualization (NFV) is seen as the key enabler towards the flexible resource management and sharing of 6G networks. The main idea of NFV is to decouple the physical devices from the specific functions that run on them. In NFV, virtual network service (NS) is modeled as a service function chain (SFC). The challenges in SFC description, composition, embedding, and scheduling are key issues in NFV. In this paper, we focus on the joint SFC embedding and scheduling for NFV in 6G networks. With the assistance of sensing the physical node resource abilities, we propose a novel SFC embedding and scheduling algorithm, which is named as RA-SFC-6G. A new service is first composed as an SFC which is an ordered sequence of virtual network functions (VNFs). Afterwards, our RA-SFC-6G algorithm will select the physical nodes with stronger resource abilities and abundant resources to accommodate the SFC. In addition, the NS is guaranteed to be implemented without violating the NS maximum allowed scheduling time. If violated, our RA-SFC-6G can re-embed and re-schedule the violated VNFs to suitable positions. In order to validate our RA-SFC-6G performance, we do the experiment work. Experiment results show that our RA-SFC-6G achieves at least 10% higher SFC acceptance ratio than the previous counterparts and the typical heuristics.
KW - 5G
KW - 6G networks
KW - embedding and scheduling
KW - NFV
KW - scheduling time
KW - service function chain
UR - http://www.scopus.com/inward/record.url?scp=85103051698&partnerID=8YFLogxK
U2 - 10.1109/TVT.2021.3065967
DO - 10.1109/TVT.2021.3065967
M3 - Journal article
AN - SCOPUS:85103051698
SN - 0018-9545
VL - 70
SP - 3846
EP - 3859
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 4
M1 - 9380157
ER -