A Power Efficient and Robust Virtual Network Functions Placement Problem

Marotta, Antonio; Kassler, Andreas

doi:10.1109/itc-28.2016.151

Cited by 31 publications

(42 citation statements)

References 12 publications

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“…For this reason, the problem of VNF placement has been attracting increasing attention during the last years [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25]. Nonetheless, the optimal placement of virtual elements to physical resources aimed at minimizing power consumption with service performance constraints for the 5G scenario under study is a complex issue.…”

Section: Related Workmentioning

confidence: 99%

“…However, it is worth mentioning the few works we have found deal with power-based VNF placement proposals [17][18][19][20][21] for our case study. Reference [17] aims at minimizing power consumption allowing users to meet delay requirements using a genetic algorithm approach, while [18,19] propose heuristic algorithms that give power reduction improvement.…”

Section: Related Workmentioning

confidence: 99%

“…In order to cope with uncertain input parameters, RO [10] is applied to solve optimization problems. Indeed, RO has been successfully employed in different contexts, such as in resource allocation in OFDM networks [26] with uncertainty in channel state information, in cloud resource provisioning without perfect knowledge of demands and price [21], and even in the virtual network embedding problem on a physical network substrate in recent works [27][28][29][30] that usually deal with uncertain service demands.…”

Section: Related Workmentioning

confidence: 99%

“…Nevertheless, to the best of our knowledge, except the work presented in [21], there is no VNF placement proposal based on RO. Therefore, to achieve our goal of designing an energy-aware placement solution using RO approach that considers service demand uncertainty, [21] has been relevant.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, to achieve our goal of designing an energy-aware placement solution using RO approach that considers service demand uncertainty, [21] has been relevant. Authors develop a novel power-based placement solution with uncertainty in VNFs CPU demands based on RO theory.…”

Section: Related Workmentioning

confidence: 99%

See 4 more Smart Citations

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

Blanco

Taboada

Fajardo

et al. 2017

Mobile Information Systems

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In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

Blanco

Taboada

Fajardo

et al. 2017

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

On Analyzing the Trade-Off Between Over-Commitment Ratio and Quality of Service in NFV Datacenter

Tran

Dang

et al. 2019

Future Data and Security Engineering

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A Survey of Resource Management in Cloud and Edge Computing

Zhang

2020

Network Management in Cloud and Edge Computing

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Due to the limited resource capacity of edge servers and the high purchase costs of edge resources, service providers are facing the new challenge of how to take full advantage of the constrained edge resources for Internet of Things (IoT) service hosting and task scheduling to maximize system performance. In this paper, we study the joint optimization problem on service placement, resource provisioning, and workloads scheduling under resource and budget constraints, which is formulated as a mixed integer non-linear programming problem. Given that the frequent service placement and resource provisioning will significantly increase system configuration costs and instability, we propose a two-timescale framework for resource management and workloads scheduling, named RMWS. RMWS consists of a Gibbs sampling algorithm and an alternating minimization algorithm to determine the service placement and resource provisioning on large timescales. And a sub-gradient descent method has been designed to solve the workload scheduling challenge on small timescales. We conduct comprehensive experiments under different parameter settings. The RMWS consistently ensures a minimum 10% performance enhancement compared to other algorithms, showcasing its superiority. Theoretical proofs are also provided accordingly.

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A Power Efficient and Robust Virtual Network Functions Placement Problem

Cited by 31 publications

References 12 publications

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

On Analyzing the Trade-Off Between Over-Commitment Ratio and Quality of Service in NFV Datacenter

A Survey of Resource Management in Cloud and Edge Computing

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