Application-Driven Provisioning of Service Function Chains Over Heterogeneous NFV Platforms

Dong, Lü; Fonseca, Nelson L. S. da; Zhu, Zuqing

doi:10.1109/tnsm.2020.3035254

Cited by 14 publications

(4 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

See 1 more Smart Citation

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

View full text Add to dashboard Cite

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.

show abstract

Section: Path Planningmentioning

confidence: 99%

“…In the NFV architecture, VNFs are implemented in software and running on NFV based equipment. When traffic arrives, it will be orderly served by VNFs, and we call these ordered VNFs as a Service Function Chain (SFC) [10,11]. Each SFC is presented as VNFs connected by virtual links.…”

Section: Introductionmentioning

confidence: 99%

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

View full text Add to dashboard Cite

show abstract

“…Although in this work, the role of SDN is not clearly explained, the proposed algorithm can be implemented in the control plane of an SDN-based NFV framework. Another work in [66] studied the same problem in a more heterogeneous environment, including software and hardware NFV platforms, such as virtual machine (VM), docker container and SmartNIC.…”

Section: Application Placement In Cloud-fogmentioning

confidence: 99%

Next Generation of SDN in Cloud-Fog for 5G and Beyond-Enabled Applications: Opportunities and Challenges

Ahvar

Raza

et al. 2021

Network

View full text Add to dashboard Cite

In recent years, the number of objects connected to the internet have significantly increased. Increasing the number of connected devices to the internet is transforming today’s Internet of Things (IoT) into massive IoT of the future. It is predicted that, in a few years, a high communication and computation capacity will be required to meet the demands of massive IoT devices and applications requiring data sharing and processing. 5G and beyond mobile networks are expected to fulfill a part of these requirements by providing a data rate of up to terabits per second. It will be a key enabler to support massive IoT and emerging mission critical applications with strict delay constraints. On the other hand, the next generation of software-defined networking (SDN) with emerging cloudrelated technologies (e.g., fog and edge computing) can play an important role in supporting and implementing the above-mentioned applications. This paper sets out the potential opportunities and important challenges that must be addressed in considering options for using SDN in hybrid cloud-fog systems to support 5G and beyond-enabled applications.

show abstract

“…The above discussion motivates the need to jointly study VNF placement alongside computational and communication resource allocation in a mobile network, while satisfying the SFC, throughput, and delay requirements [7][8][9]. In addition, B5G is expected to include a variety of different access and transport technologies with distinct characteristics that should be jointly studied.…”

Section: Introductionmentioning

confidence: 99%

Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

et al. 2021

View full text Add to dashboard Cite

In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.

show abstract

Application-Driven Provisioning of Service Function Chains Over Heterogeneous NFV Platforms

Cited by 14 publications

References 47 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

Next Generation of SDN in Cloud-Fog for 5G and Beyond-Enabled Applications: Opportunities and Challenges

Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

Contact Info

Product

Resources

About