User mobility-aware Virtual Network Function placement for Virtual 5G Network Infrastructure

Taleb, Tarik; Bagaa, Miloud; Ksentini, Adlen

doi:10.1109/icc.2015.7248929

Cited by 111 publications

(60 citation statements)

References 15 publications

(24 reference statements)

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“…These virtual devices in the network will work as a physical device, and can achieve a variety of specialized functions without a specific device [36][37][38][39]. Currently, NFV mainly focus on the following issues.…”

Section: Nfvmentioning

confidence: 99%

Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies

et al. 2015

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In recent years, information communication and computation technologies are deeply converging, and various wireless access technologies have been successful in deployment. It can be predicted that the upcoming fifthgeneration mobile communication technology (5G) can no longer be defined by a single business model or a typical technical characteristic. 5G is a multi-service and multitechnology integrated network, meeting the future needs of a wide range of big data and the rapid development of numerous businesses, and enhancing the user experience by providing smart and customized services. In this paper, we propose a cloud-based wireless network architecture with four components, i.e., mobile cloud, cloud-based radio access network (Cloud RAN), reconfigurable network and big data centre, which is capable of providing a virtualized, reconfigurable, smart wireless network.

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Section: Nfvmentioning

confidence: 99%

Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies

et al. 2015

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“…On the other hand, in the MEC area, authors in [18], [20] propose an approach to dynamically place network functions [16], [20] × (predefined) × × [17], [18], [21] × × [19], [22] × × × Our work on MEC servers available in mobile base stations, according to the handover probability of users for the next time-slot. They formulate two optimization models with the objective of minimizing network function migrations and communication cost (i.e., QoS/QoE) between users (UEs) and network functions.…”

Section: Related Workmentioning

confidence: 99%

Mobility-Aware Joint Service Placement and Routing in Space-Air-Ground Integrated Networks

Varasteh

Hofmann

Ðerić

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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People desire to be connected, no matter where they are. Recently, providing Internet access to on-board passengers has received a lot of attention from both industry and academia. However, in order to guarantee an acceptable Quality of Service (QoS) for the passenger services with low incurred cost, the path to route the services, as well as the datacenter (DC) to deploy the services should be carefully determined. This problem is challenging, due to different types of Air-to-Ground (A2G) connections, i.e., satellites and Direct Air-To-Ground (DA2G) links. These A2G connection types differ in terms of cost, bandwidth, and latency. Furthermore, due to the flights' movements, it is important to consider adapting the service location accordingly. In this work, we formulate two Mixed Integer Linear Programs (MILPs) for the problem of Joint Service Placement and Routing (JSPR): i) Static (S-JSPR), and ii) Mobility-Aware (MA-JSPR) in Space-Air-Ground Integrated Networks (SAGIN), with the objective of minimizing the total cost. We compare S-JSPR and MA-JSPR using comprehensive evaluations in a realistic European-based SAGIN. The obtained results show that the MA-JSPR model, by considering the future flight positions and using a service migration control, reduces the long-term total cost notably. Also, we show S-JSPR benefits from a low time-complexity and it achieves lower end-to-end delays comparing to MA-JSPR model.

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“…The authors in [11] propose VNF placement algorithms with two-fold objective of minimizing path between users and data anchor gateways, and optimizing the sessions' mobility. In [12] the authors propose a time-efficient heuristic based on affiliation-aware VNF placement for NS deployment.…”

Section: Related Workmentioning

confidence: 99%

z-TORCH: An Automated NFV Orchestration and Monitoring Solution

Sciancalepore¹,

Yousaf²,

Costa‐Pérez³

2018

IEEE Trans. Netw. Serv. Manage.

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Autonomous management and orchestration (MANO) of virtualized resources and services, especially in large-scale Network Function Virtualization (NFV) environments, is a big challenge owing to the stringent delay and performance requirements expected of a variety of network services. The Quality-of-Decisions (QoD) of a Management and Orchestration (MANO) system depends on the quality and timeliness of the information received from the underlying monitoring system. The data generated by monitoring systems is a significant contributor to the network and processing load of MANO systems, impacting thus their performance. This raises a unique challenge: how to jointly optimize the QoD of MANO systems while at the same minimizing their monitoring loads at runtime? This is the main focus of this paper.In this context, we propose a novel automated NFV orchestration solution, namely z-TORCH (zero Touch Orchestration) that jointly optimizes the orchestration and monitoring processes by exploiting machine-learning-based techniques. The objective is to enhance the QoD of MANO systems achieving a near-optimal placement of Virtualized Network Functions (VNFs) at minimum monitoring costs.

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User mobility-aware Virtual Network Function placement for Virtual 5G Network Infrastructure

Cited by 111 publications

References 15 publications

Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies

Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies

Mobility-Aware Joint Service Placement and Routing in Space-Air-Ground Integrated Networks

z-TORCH: An Automated NFV Orchestration and Monitoring Solution

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