Service Function Graph Design and Mapping for NFV with Priority Dependence

Jalalitabar, Maryam; Luo, Guangchun; Kong, Chenguang; Cao, Xiaojun

doi:10.1109/glocom.2016.7842263

Cited by 16 publications

(8 citation statements)

References 10 publications

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“…The placement of VNFs with dependency and traffic volume scaling has been studied in several articles. Jalalitabar et al [22,35] proposed an efficient way to design users service requests while considering the computing resource, VNF dependency and service request. Ye et al [15] proposed a heuristic algorithm to solve the multiple SFCs design, optimize the network reconfigurations and protect the service steadiness.…”

Section: Related Workmentioning

confidence: 99%

“…Next, we put the source node src f into the queue Queue (line 5). After that it selects the node x with the lowest estimated cost in the queue to determine whether the node is the destination node and the number of times it exits the queue is k. If so, the current path is the k − th shortest path from the source node to the destination node, and the algorithm ends (lines [6][7][8][9][10][11][12][13][14][22][23][24]. Otherwise, the algorithm searches the adjacent nodes of node x, and add the information of them to the priority queue (lines 15-21).…”

Section: Path Planningmentioning

confidence: 99%

“…Another important factor for SFC design is the dependency between VNFs, which means that the VNFs of a flow have constraints on the order. If VNF a depends on VNF b, the traffic flow must be processed by b before passing through a [22]. For example, if a traffic flow needs to be securely connected to the Internet, it should traverse through an encryptor and transmit to the network before the decryption function is started [14,23].…”

Section: Introductionmentioning

confidence: 99%

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SFC Design and VNF Placement Based on Traffic Volume Scaling and VNF Dependency in 5G Networks

Zeng¹,

Xia²,

Zhang³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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The development of Fifth-Generation (5G) mobile communication technology has remarkably promoted the spread of the Internet of Things (IoT) applications. As a promising paradigm for IoT, edge computing can process the amount of data generated by mobile intelligent devices in less time response. Network Function Virtualization (NFV) that decouples network functions from dedicated hardware is an important architecture to implement edge computing, deploying heterogeneous Virtual Network Functions (VNF) (such as computer vision, natural language processing, intelligent control, etc.) on the edge service nodes. With the NFV MANO (Management and Orchestration) framework, a Service Function Chain (SFC) that contains a set of ordered VNFs can be constructed and placed in the network to offer a customized network service. However, the procedure of NFV orchestration faces a technical challenge in minimizing the network cost of VNF placement due to the complexity of the changing effect of traffic volume and the dependency on the VNF relationship. To this end, we jointly optimize SFC design and VNF placement to minimize resource cost while taking account of VNF dependency and traffic volume scaling. First, the problem is formulated as an Integer Linear Programming (ILP) model and proved NPhard by reduction from Hamiltonian Cycle problem. Then we proposed an efficient heuristic algorithm called Traffic Aware and Interdependent VNF Placement (TAIVP) to solve the problem. Compared with the benchmark algorithms, emulation results show that our algorithm can reduce network cost by 10.2% and increase service request acceptance rate by 7.6% on average.

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Section: Related Workmentioning

confidence: 99%

Section: Path Planningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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SFC Design and VNF Placement Based on Traffic Volume Scaling and VNF Dependency in 5G Networks

Zeng¹,

Xia²,

Zhang³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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“…With multiple SFCs, the corresponding SFC forwarding graph identified in forms a fork network structure. Extending from NFP‐1SFC, we study the approximation algorithm for SFC‐Fork, where multiple SFC chains share the common structure.…”

Section: Solution Approachmentioning

confidence: 99%

“…The first set of problems is a fundamental problem in NFV which helps establish the end‐to‐end route to fulfill NF requests. The second set has SFC‐Fork as the NF forwarding graph, which is the commonly established forwarding graph in NFV 5G implementation (see ). To address these problems, we construct an auxiliary NF‐enabled network that serves as an intermediate layer between the NF forwarding graph and the physical substrate network and provides all possible connections among NF‐enabled nodes.…”

Section: Introductionmentioning

confidence: 99%

Robust network function virtualization

Lin

Zhou²

2020

Networks

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Network function virtualization (NFV) enables on‐demand network function (NF) deployment providing agile and dynamic network services. Through an evaluation metric that quantifies the minimal reliability among all NFs for all demands, service providers and operators may better facilitate flexible NF service recovery and migration, thus offering higher service reliability. In this paper, we present evaluation metrics on NFV reliability and solution approaches to solve robust NFV under random NF‐enabled node failure(s). We demonstrate how to construct an auxiliary NF‐enabled network and its mapping onto the physical substrate network. With the constructed NF‐enabled network, we develop pseudo‐polynomial algorithms to solve the robust NF and SFC s − t path problems: subproblems of robust NFV. We also present approximation algorithms for robust NFV with the SFC‐Fork as the NF forwarding graph. Furthermore, we propose exact solution approaches via mixed‐integer linear programming under the general setting. Computational results show that our proposed solution approaches are capable of managing robust NFV in a large‐size network.

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Low-latency orchestration for workflow-oriented service function chain in edge computing

Sun

et al. 2018

Future Generation Computer Systems

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Service Function Graph Design and Mapping for NFV with Priority Dependence

Cited by 16 publications

References 10 publications

SFC Design and VNF Placement Based on Traffic Volume Scaling and VNF Dependency in 5G Networks

SFC Design and VNF Placement Based on Traffic Volume Scaling and VNF Dependency in 5G Networks

Robust network function virtualization

Low-latency orchestration for workflow-oriented service function chain in edge computing

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