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Scientific Article details

Title Large-Scale Service Function Chaining Management and Orchestration in Smart City
ID_Doc 35854
Authors Tam, P; Kang, SW; Ros, S; Song, IS; Kim, S
Title Large-Scale Service Function Chaining Management and Orchestration in Smart City
Year 2023
Published Electronics, 12, 19
DOI 10.3390/electronics12194018
Abstract In the core networking of smart cities, mobile network operators need solutions to reflect service function chaining (SFC) orchestration policies while ensuring efficient resource utilization and preserving quality of service (QoS) in large-scale networking congestion states. To offer this solution, we observe the standardized QoS class identifiers of smart city scenarios. Then, we reflect the service criticalities via cloning virtual network function (VNF) with reserved resources for ensuring effective scheduling of request queue management. We employ graph neural networks (GNN) with a message-passing mechanism to iteratively update hidden states of VNF nodes with the objectives of enhancing allocation of resource blocks, accurate detection of availability statuses, and duplication of heavily congested instances. The deployment properties of smart city use cases are presented along with their intelligent service functions, and we aim to activate a modular architecture with multi-purpose VNFs and chaining isolation for generalizing global instances. Experimental simulation is conducted to illustrate how the proposed scheme performs under different congestion levels of SFC request rates, while capturing the key performance metrics of average delay, acceptance ratios, and completion ratios.
Author Keywords graph neural networks; quality of service; service function chaining; smart city; virtual network functions
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:001145739100001
WoS Category Computer Science, Information Systems; Engineering, Electrical & Electronic; Physics, Applied
Research Area Computer Science; Engineering; Physics
PDF https://www.mdpi.com/2079-9292/12/19/4018/pdf?version=1695604470
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