Application and Network VNF migration in a MEC-enabled 5G Architecture

Sarrigiannis, Ioannis; Kartsakli, Elli; Ramantas, Kostas; Antonopoulos, Angelos; Verikoukis, Christos

doi:10.1109/camad.2018.8514943

Cited by 30 publications

(26 citation statements)

References 8 publications

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“…Recent development with regards to 5G network slicing in MEC and/or cloud/Fog computing domain include [295][296][297][298][299] . Authors in [295] present a MEC-enabled 5G architecture that supports the flexible placement/migration of network and application VNFs. NFVO orchestrates the VNFs with admission control and management capabilities that can manage the NFs and resources on-the-fly.…”

Section: Network Slicing Management In Edge/cloud and Fog Computingmentioning

confidence: 99%

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

et al. 2020

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a b s t r a c tThe increasing consumption of multimedia services and the demand of high-quality services from customers has triggered a fundamental change in how we administer networks in terms of abstraction, separation, and mapping of forwarding, control and management aspects of services. The industry and the academia are embracing 5G as the future network capable to support next generation vertical applications with different service requirements. To realize this vision in 5G network, the physical network has to be sliced into multiple isolated logical networks of varying sizes and structures which are dedicated to different types of services based on their requirements with different characteristics and requirements (e.g., a slice for massive IoT devices, smartphones or autonomous cars, etc.). Softwarization using Software-Defined Networking (SDN) and Network Function Virtualization (NFV)in 5G networks are expected to fill the void of programmable control and management of network resources.In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirements followed by a description of 5G network softwarization and slicing paradigms including essential concepts, history and different use cases. Secondly, we provide a tutorial of 5G network slicing technology enablers including SDN, NFV, MEC, cloud/Fog computing, network hypervisors, virtual machines & containers. Thidly, we comprehensively survey different industrial initiatives and projects that are pushing forward the adoption of SDN and NFV in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions and deployment strategies is presented. Moreover, we provide a discussion on various open source orchestrators and proof of concepts representing industrial contribution. The work also investigates the standardization efforts in 5G networks regarding network slicing and softwarization. Additionally, the article presents the management and orchestration of network slices in a single domain followed by a comprehensive survey of management and orchestration approaches in 5G network slicing across multiple domains while supporting multiple tenants. Furthermore, we highlight the future challenges and research directions regarding network softwarization and slicing using SDN and NFV in 5G networks.Crown (A .A . Barakabitze). tems [1,2,3] . The increasing number of smart devices (e.g., tablets and smartphones) and the growing number of bandwidth-hungry mobile applications (e.g., live video streaming, online video gaming) which demand higher spectral efficiency than that of 4G systems are posing significant challenges in 5G. The Cisco Visual Networking Index (VNI) Forecast [4] predicts that IP video traffic will be 82% of all consumer Internet traffic by 2022, up from 75% in 2017. Mobile video traffic alone will account for 78% of the global mobile data traffic. W...

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Section: Network Slicing Management In Edge/cloud and Fog Computingmentioning

confidence: 99%

5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges

et al. 2020

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“…Considering the very low latency required by uRLLC services, the algorithm tries to find a tradeoff between low service latency and high availability. To maximize the utilization of the MEC resources for low latency applications, a seamless application and VNF migration approach is presented in [39]. In this approach, if the NFV orchestrator accepts a request that has a predefined network and computation resource requirements, it determines where the accepted request should be executed and then migrates the application or the VNF.…”

Section: Flexibility and Fast Deployment Of New Servicesmentioning

confidence: 99%

Multi-Access Edge Computing: A Survey

et al. 2020

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Multi-access Edge Computing (MEC) is a key solution that enables operators to open their networks to new services and IT ecosystems to leverage edge-cloud benefits in their networks and systems. Located in close proximity from the end users and connected devices, MEC provides extremely low latency and high bandwidth while always enabling applications to leverage cloud capabilities as necessary. In this paper, we illustrate the integration of MEC into a current mobile networks' architecture as well as the transition mechanisms to migrate into a standard 5G network architecture. We also discuss SDN, NFV, SFC and network slicing as MEC enablers. Then, we provide a state-of-the-art study on the different approaches that optimize the MEC resources and its QoS parameters. In this regard, we classify these approaches based on the optimized resources and QoS parameters (i.e., processing, storage, memory, bandwidth, energy and latency). Finally, we propose an architectural framework for a MEC-NFV environment based on the standard SDN architecture.

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“…A similar approach but focused on vehicular networks is presented in [13], paying special attention to the selection of diverse wireless RATs using SDN. MEC is used in [14] for both application and network planes, but it also considers the migration of virtual network functions (VNFs) along the network hierarchy according to the system load. The allocation and migration of VNFs is being widely studied using formal methods, as can be seen in [15]- [17] considering parameters such as the computing load and network performance.…”

Section: State Of the Artmentioning

confidence: 99%