Cost-Oriented and Delay-Constrained Anycasting for Service Function Chain Provisioning Leveraging Cloud–Edge Collaboration in Space–Air–Ground Integrated Networks

Network function virtualization (NFV) offers a flexible and effective means to utilize heterogeneous resources for space-air–ground integrated networks (SAGINs), enabling seamless connectivity for data transmission over large spans. Converging the cloud and edge computing capabilities, SAGINs have the potential to further provision service function chains (SFCs) with various Internet applications. This is driving the need for efficient schemes of the cloud- or edge-based services in SAGINs. In this article, we propose a novel SAGIN architecture based on the cloud-serving and edge-processing collaboration. The cloud-based services are provisioned by the selected ground data centers (DCs), in which the traffic is processed by the virtual network function (VNF) hosted in the edge nodes and DCs. In such an architecture, the edge nodes enable flexible SFC provisioning solutions while DCs offer a variety of cloud-oriented network services. In addition, we apply anycast to further improve the agility of SFC provisioning. From these perspectives, we investigate the cloud-serving and edge-processing SFC provisioning problem leveraging anycast, concerning DC assignment, edge and VNF placement, SFC mapping, and delay constraints simultaneously. The joint problem is formulated by a mixed integer linear program (MILP) model to jointly minimize the communication and computation costs subject to their tradeoff. A decomposition approach is further developed for the sake of scalability. Results from numerical simulations show that the proposed approach can reduce overall costs by up to 32.99%.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-10-24
DOI
https://doi.org/10.1109/jiot.2024.3485640
Citations
3
Primary Topic
Satellite Communication Systems
Type
article
Field-Weighted Citation Impact
3.90
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article

Cost-Oriented and Delay-Constrained Anycasting for Service Function Chain Provisioning Leveraging Cloud–Edge Collaboration in Space–Air–Ground Integrated Networks

Yuxuan He, Min Ju, Yuanhao Liu, Kai Zhang et al.
3 citations
IEEE Internet of Things Journal
Satellite Communication Systems
3.90
article

Cost-Oriented and Delay-Constrained Anycasting for Service Function Chain Provisioning Leveraging Cloud–Edge Collaboration in Space–Air–Ground Integrated Networks

Yuxuan He, Min Ju, Yuanhao Liu, Kai Zhang, Yongjun Li, Xiang Wang, Tian Qin, Zhiqiang Ma
article en
3 citations

Abstract

Network function virtualization (NFV) offers a flexible and effective means to utilize heterogeneous resources for space-air–ground integrated networks (SAGINs), enabling seamless connectivity for data transmission over large spans. Converging the cloud and edge computing capabilities, SAGINs have the potential to further provision service function chains (SFCs) with various Internet applications. This is driving the need for efficient schemes of the cloud- or edge-based services in SAGINs. In this article, we propose a novel SAGIN architecture based on the cloud-serving and edge-processing collaboration. The cloud-based services are provisioned by the selected ground data centers (DCs), in which the traffic is processed by the virtual network function (VNF) hosted in the edge nodes and DCs. In such an architecture, the edge nodes enable flexible SFC provisioning solutions while DCs offer a variety of cloud-oriented network services. In addition, we apply anycast to further improve the agility of SFC provisioning. From these perspectives, we investigate the cloud-serving and edge-processing SFC provisioning problem leveraging anycast, concerning DC assignment, edge and VNF placement, SFC mapping, and delay constraints simultaneously. The joint problem is formulated by a mixed integer linear program (MILP) model to jointly minimize the communication and computation costs subject to their tradeoff. A decomposition approach is further developed for the sake of scalability. Results from numerical simulations show that the proposed approach can reduce overall costs by up to 32.99%.

IEEE Internet of Things JournalVol. 12(4)
Nanjing Audit University (CN), Air Force Engineering University (CN), Xi’an University of Posts and Telecommunications (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Satellite Communication Systems
3.90
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