TY - GEN
T1 - IoT-centric service function chainingorchestration and its performance validation
AU - Sekine, Hibiki
AU - Kanai, Kenji
AU - Katto, Jiro
AU - Kanemitsu, Hidehiro
AU - Nakazato, Hidenori
N1 - Funding Information:
TIllS paper is partially supported by the ED-JAPAN initiative by the EC Horizon 2020 Work Programme (2018-2020) Grant Agreement No. 81-1918 and Ministry of Internal Affairs and Communications "Federating loT and cloud infrastructures 10 provide scalable and interoperable Smart Cities applications. by introducing novel loT virtualization technologies (Fed-llo'T) (JPJ000595)"". In addition. this paper is also partial ly support by the veri fication-style research & development program for solving reginal challenges using data cooperation and utilization by :NICT. Japan and partially SUPPOlted by the R&D contract "Wired-and-wireless Converged Radio Access Network for Massive loT Traffic (JPJO00254r' with the Ministry of Internal Affairs and Communications. Japan. for radio resource enhancement
Publisher Copyright:
© 2021 IEEE.
PY - 2021/1/9
Y1 - 2021/1/9
N2 - In order to simplify deployment and management of IoT services, Network Function Virtualization (NFV) and Service Function Chaining (SFC) are promising solutions, and much researchers have conducted these topics. To enhance the reliability of former research efforts, in this paper, we propose an orchestration framework for IoT-centric SFC by using Docker and Kubernetes. The framework enables an automatic IoT service deployment by satisfying service requirements and computing and network resource constraints. In such deployment, we apply a Virtual Network Function (VNF)/Service Function (SF) placement problem to achieve efficient utilization of the resources. We set an objective function as minimizing both numbers of SF instances and communications and build a mathematical model based on Integer Linear Programming (ILP). To validate it, we implement a model for the framework and evaluate the performances by carrying out a numerical evaluation and a real experiment. From the evaluation results, we confirm that the proposed approach can reduce the number of SF placements and the number of communications among SF instances.
AB - In order to simplify deployment and management of IoT services, Network Function Virtualization (NFV) and Service Function Chaining (SFC) are promising solutions, and much researchers have conducted these topics. To enhance the reliability of former research efforts, in this paper, we propose an orchestration framework for IoT-centric SFC by using Docker and Kubernetes. The framework enables an automatic IoT service deployment by satisfying service requirements and computing and network resource constraints. In such deployment, we apply a Virtual Network Function (VNF)/Service Function (SF) placement problem to achieve efficient utilization of the resources. We set an objective function as minimizing both numbers of SF instances and communications and build a mathematical model based on Integer Linear Programming (ILP). To validate it, we implement a model for the framework and evaluate the performances by carrying out a numerical evaluation and a real experiment. From the evaluation results, we confirm that the proposed approach can reduce the number of SF placements and the number of communications among SF instances.
KW - Network Function Virtualization(NFV)
KW - Service Function Chaining (SFC)
KW - VNF/SFC placement Orchestration
UR - http://www.scopus.com/inward/record.url?scp=85102980846&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102980846&partnerID=8YFLogxK
U2 - 10.1109/CCNC49032.2021.9369538
DO - 10.1109/CCNC49032.2021.9369538
M3 - Conference contribution
AN - SCOPUS:85102980846
T3 - 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
BT - 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021
Y2 - 9 January 2021 through 13 January 2021
ER -