A Survey on the Placement of Virtual Resources and Virtual Network Functions

Laghrissi, Abdelquoddouss; Taleb, Tarik

doi:10.1109/comst.2018.2884835

Cited by 229 publications

(141 citation statements)

References 142 publications

(161 reference statements)

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“…SA3 21 http://5gaa.org/ . 22 WG specifies security capabilities of E2E network slicing that require triggering, and coordination with the ETSI ISG NFV on the isolation of network slices [14] . The 3GPP SA5 defines the management of slices in coordination with other relevant SDOs to generate a complete E2E network slice.…”

Section: Gppmentioning

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: Gppmentioning

confidence: 99%

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

et al. 2020

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“…NFEP can be solved via using mathematical methods or by designing a heuristic algorithm. Although mathematical models provide an optimal solution, they are complex and proven to be NP-hard [2]. The alternative is to design a heuristic that can provide near-optimal solutions with less computational demand and near optimal performance.…”

Section: Related Workmentioning

confidence: 99%

The Value of Simple Heuristics for Virtualized Network Function Placement

Jahedi¹,

Kunz²

2020

Future Internet

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Network Function Virtualization (NFV) can lower the CAPEX and/or OPEX for service providers and allow for quick deployment of services. Along with the advantages come some challenges. The main challenge in the use of Virtualized Network Functions (VNF) is the VNFs’ placement in the network. There is a wide range of mathematical models proposed to place the Network Functions (NF) optimally. However, the critical problem of mathematical models is that they are NP-hard, and consequently not applicable to larger networks. In wireless networks, we are considering the scarcity of Bandwidth (BW) as another constraint that is due to the presence of interference. While there exist many efforts in designing a heuristic model that can provide solutions in a timely manner, the primary focus with such heuristics was almost always whether they provide results almost as good as optimal solution. Consequently, the heuristics themselves become quite non-trivial, and solving the placement problem for larger networks still takes a significant amount of time. In this paper, in contrast, we focus on designing a simple and scalable heuristic. We propose four heuristics, which are gradually becoming more complex. We compare their performance with each other, a related heuristic proposed in the literature, and a mathematical optimization model. Our results demonstrate that while more complex placement heuristics do not improve the performance of the algorithm in terms of the number of accepted placement requests, they take longer to solve and therefore are not applicable to larger networks.In contrast, a very simple heuristic can find near-optimal solutions much faster than the other more complicated heuristics while keeping the number of accepted requests close to the results achieved with an NP-hard optimization model.

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“…VNF placement: In NFV, the placement of VNF instances often has a significant impact on system performances [27] [42]. Insights from such works can be combined with our schemes to achieve even better performance.…”

Section: A Optimizing Nfv/vnf From Different Aspectsmentioning

confidence: 99%

“…By substituting (28) into (27), canceling the terms irrelevant to the decision variables µ(t), X(t), and Y (t), we obtain…”

Section: Proof Of Lemmamentioning

confidence: 99%

“…Given that VNF placement is considered static at the time scale of flow or request operations [27], for service chaining and resource scheduling, a natural question is: should they also be static, or dynamic? Static schemes have been implemented in some scenarios [18], but often times request traffic is highly fluctuating in both temporal and spatial dimensions [25].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Online VNF Chaining and Scheduling with Prediction: Optimality and Trade-Offs

Huang

Bian

Gao

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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For NFV systems, the key design space includes the function chaining for network requests and the resource scheduling for servers. The problem is challenging since NFV systems usually require multiple (often conflicting) design objectives and the computational efficiency of real-time decision making with limited information. Furthermore, the benefits of predictive scheduling to NFV systems still remain unexplored. In this paper, we propose POSCARS, an efficient predictive and online service chaining and resource scheduling scheme that achieves tunable trade-offs among various system metrics with stability guarantee. Through a careful choice of granularity in system modeling, we acquire a better understanding of the tradeoffs in our design space. By a non-trivial transformation, we decouple the complex optimization problem into a series of online sub-problems to achieve the optimality with only limited information. By employing randomized load balancing techniques, we propose three variants of POSCARS to reduce the overheads of decision making. Theoretical analysis and simulations show that POSCARS and its variants require only mild-value of future information to achieve near-optimal system cost with ultra-low request response time.

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A Survey on the Placement of Virtual Resources and Virtual Network Functions

Cited by 229 publications

References 142 publications

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

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

The Value of Simple Heuristics for Virtualized Network Function Placement

Online VNF Chaining and Scheduling with Prediction: Optimality and Trade-Offs

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