NFV and SFC: A Case Study of Optimization for Virtual Mobility Management

Jin, Hao; Jin, Yi; Lu, Haiya; Zhao, Chenglin; Peng, Mugen

doi:10.1109/jsac.2018.2869967

Cited by 14 publications

(14 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Jin et al [49] also considered cellular networks, but the SFC was a general signaling processing flow of virtual Mobility Management Entity (vMME) from LTE (4G). Several cost functions were minimized in the proposed problem: the total signaling communication overhead cost; signaling communication overhead cost on backhauls; and migration overhead cost.…”

Section: Multi-objectivementioning

confidence: 99%

See 1 more Smart Citation

Service Function Chain Placement in Distributed Scenarios: A Systematic Review

et al. 2021

View full text Add to dashboard Cite

The network function virtualization (NFV) paradigm is an emerging technology that provides network flexibility by allowing the allocation of network functions over commodity hardware, like legacy servers in an IT infrastructure. In comparison with traditional network functions, implemented by dedicated hardware, the use of NFV reduces the operating and capital expenses and improves service deployment. In some scenarios, a complete network service can be composed of several functions, following a specific order, known as a service function chain (SFC). SFC placement is a complex task, already proved to be NP-hard. Moreover, in highly distributed scenarios, the network performance can also be impacted by other factors, such as traffic oscillations and high delays. Therefore, a given SFC placement strategy must be carefully developed to meet the network operator service constraints. In this paper, we present a systematic review of SFC placement advances in dis-

show abstract

Section: Multi-objectivementioning

confidence: 99%

“…The smart city scenario was considered in [55], [49], [85], and [111]. This type of scenario has interesting dynamic characteristics due to the high mobility of users, which were presented as one of the major challenges in the SFC placement [49].…”

Section: Scenariosmentioning

confidence: 99%

Service Function Chain Placement in Distributed Scenarios: A Systematic Review

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In the perspective of research on virtual mobility management, there has been some research issues on the placement of vMME/vEPC NFs. Some of them focus on the mapping of vEPC [7][8][9][10][11][12][13], which mainly related to the optimization of mobility management on data plane, while others concentrate on the mapping of vMME [7,[11][12][13][14][15] and optimal placement of mobility management related VNFs. For example, in [7], the placement of virtual network slice is proposed over a federated cloud by deploying the virtual instances of key vEPC NFs considering both 4G and new N-Fs of 5G.…”

Section: The Key Laboratory Of Universal Wireless Communications For mentioning

confidence: 99%

“…In [8], the concept of soft Evolved Packet Core (softEPC) is presented to instantiate the virtual network functions of EPC flexibly and dynamically over a physical network topology. Regarding the optimization objects, operation cost, load balancing and delay/response time are major objectives in these issues [7,11,12,14].…”

Section: The Key Laboratory Of Universal Wireless Communications For mentioning

confidence: 99%

AMF Optimal Placement based on Deep Reinforcement Learning in Heterogeneous Radio Access Network

Hao

Pang

Zhao

2020

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract To support various service requirements such as massive Machine Type Communications, Ultra-Reliable and Low-Latency Communications in 5G scenario, Network Function Virtualization (NFV) plays an important role in the 5G network architecture to manage and orchestrate network services. As the key network function responsible for mobility management, Access and Mobility Management Function (AMF) can be deployed flexibly at the edge of the radio access network to improve the performance of mobility management based on NFV. In this paper, the optimal placement of AMF is addressed based on Deep Reinforcement Learning (DRL) in a heterogeneous radio access network, which aims to minimize the network utility including the average delay of mobility management requests at AMF, the average wired hops to relay the requests and the cost of AMF instances. By considering time-varying features including user mobility and the arrival rate of user mobility management requests, an AMF optimal placement approach is proposed for the long term optimization. Simulation results show that the performance of the proposed DRL based AMF optimal placement approach outperforms that of the baselines.

show abstract

“…The mobility between them is one of the important characteristics in the technology of management, framework and transmission path, etc. MME (Jin et al 2010) appears to be one of the promising technologies that are related to mobility problems, such as multi-homing and ID/location (radio locator) distribution. This paper proposes a new mobility management framework.…”

Section: Introductionmentioning

confidence: 99%

Design and performance evaluation of cost-effective function-distributed mobility management scheme for software-defined smart factory networking

Kim

Park

Jeong

2019

J Ambient Intell Human Comput

View full text Add to dashboard Cite

With the proliferation of mobile devices, Internet of Things (IoT), and edge commuting, and the advancement of ICT, mobile computing has become the norm, rather than the exception. Current network technologies and distributed system architectures make it difficult to meet users' network trace, and incur high processing costs. To solve this problem, this paper proposes new functional distributed mobility management technologies for the application of the industrial future Internet. This implies the need for an efficient distributed mobility system to apply 5G or TSN (time sensitive network) technologies to the future industry Internet. Thus, it is assumed that various analytical techniques will be applied to provide superior performance in cost analyses, such as location update costs and packet transport costs. In this paper, we propose a cost-effective functiondistribution mobility management system that will build a future industrial Internet to meet the needs and convenience of users. It also uses computer simulation to create the mobility provision system, and the electiveness of the cost analysis usage and rental management function models. Software-defined networking in smart factories (SFs) enables them to easily adapt the communication network to changing requirements. Similar to cloud-based systems, such SFs could be seen as producing clusters that could be rented and configured as needed. To achieve the required flexibility, the SF network uses software defined networking combined with network function virtualization. Despite the fact that the technology is not yet ready for deployment in today's manufacturing networks, a novel network architecture for SFs based on software-defined networking and network virtualization is here proposed, to support smart services, especially for Industry 4.0.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

show abstract

NFV and SFC: A Case Study of Optimization for Virtual Mobility Management

Cited by 14 publications

References 23 publications

Service Function Chain Placement in Distributed Scenarios: A Systematic Review

Service Function Chain Placement in Distributed Scenarios: A Systematic Review

AMF Optimal Placement based on Deep Reinforcement Learning in Heterogeneous Radio Access Network

Design and performance evaluation of cost-effective function-distributed mobility management scheme for software-defined smart factory networking

Contact Info

Product

Resources

About