Server Resource Dimensioning and Routing of Service Function Chain in NFV Network Architectures

Eramo, V.; Tosti, Alessandro; Miucci, E.

doi:10.1155/2016/7139852

Cited by 38 publications

(19 citation statements)

References 20 publications

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“…Thus, optimal placement of cloudlets over wireless access networks and placement of optimal number of VMs in cloudlets appeared to be essential research problems to several researchers because these aspects improve the cloudlet resource utilization significantly [12]. Note that, before the genesis of cloudlets and other edge-computing paradigms, researchers explored various VM migration techniques to optimize the power consumption in Network Function Virtualization (NFV) environments under a dynamic traffic scenario and became aware of its potential benefits [13,14]. The authors of [15] proposed a linear programming solution for computation offloading by considering the QoS requirements of mobile users while maximizing the revenue of service providers.…”

Section: Related Workmentioning

confidence: 99%

An Analytical Cost-Optimal Cloudlet Placement Framework over Fiber-Wireless Networks with Quasi-Convex Latency Constraint

2019

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To meet the low-latency constraints arising from future smart mobile devices, Internet-of-Things, and 5G applications, major interest is currently given to the integration of centralized cloud computing and distributed edge computing infrastructures to deliver higher performance and reliability to edge devices in accessing mobile cloud services. The three-tier network architecture arising from cloud, cloudlet, and edge-devices can handle miscellaneous latency requirements for both latency-sensitive and latency-tolerant applications more efficiently than conventional two-tier networks. In this paper, we primarily focus on the static cloudlet network planning problem and propose an analytical hybrid cost-optimization framework for optimal cloudlet placement. We formulate this problem as a convex optimization problem and solve by using Karush-Kuhn-Tucker (KKT) conditions, and show that this framework can be evaluated without any scalability issues observed with integer programming based frameworks for large datasets. Moreover, we derive user-friendly closed form expressions that provide a first-hand estimation of cloudlet deployment cost depending on a few important network parameters like split-ratio, population density, and network bandwidth. Finally, we also show that the optimal solution of this analytical framework can be considered as a tight lower bound of the optimal solutions of integer programming based frameworks and makes a better cloudlet installation cost estimation compared to other existing frameworks.Electronics 2019, 8, 404 2 of 18 of cloudlet computing similar to fog and mobile-edge computing, where cloudlets are considered as trusted, resource-rich computer or cluster of computers. Nonetheless, cloudlets are designed to be self-managing and function with low-context-awareness. Hence, they are most suitable for deployment in adversarial environments [3].The authors of [4] showed that the system performance in terms of expected latency for the requested jobs from a single-hop cloudlet server is always better than a distant cloud server for low-latency applications. Thus, the optimal placement of cloudlets over wireless access networks seemed to be an important research problem to enhance the system performance. Along with the wireless access networks, researchers started to focus on optical and fiber-wireless (FiWi) access networks for edge-computing solutions deployment due to their wide deployment coverage, low cost per bit, very high data transmission bandwidth, efficient network virtualization and network scalability [5]. The time-division multiplexed passive optical network (TDM-PON) has also been considered as a front/back-haul support for wireless access network, i.e., access technologies like Radio-over-Fiber (RoF), WiFi, LTE-A and millimeter-wave (mmWave) can be integrated with optical network units (ONUs) for a higher user coverage [6].A static cloudlet placement framework considers that the network is static in time, i.e., it does not consider user mobility and virtual machine (VM) mobil...

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Section: Related Workmentioning

confidence: 99%

An Analytical Cost-Optimal Cloudlet Placement Framework over Fiber-Wireless Networks with Quasi-Convex Latency Constraint

2019

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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. Besides, [20] presents a suboptimal placement solution that combines traffic and energy cost optimization derived by means of a Markov approximation with matching theory.…”

Section: Related Workmentioning

confidence: 99%

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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“…Perumal and Murugaiyan [26] have adopted an optimization technique to address the problems of VM placement and consolidation of the server. Eramo et al [27] have presented a unique architecture to solve the problem of dimensioning of server resources using optimization technique. The study outcome was found to possess better energy saving features.…”

Section: A Backgroundmentioning

confidence: 99%

Framework of Resource Management using Server Consolidation to Minimize Live Migration and Load Balancing

Ngenzi¹,

Selvarani²,

Suchithra³

2016

ijacsa

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Abstract-Live Migration is one of the essential operations that require more attention to addressing its high variability problems with virtual machines. We review the existing techniques of resource management to find that there are less modeling to solve this problem. The present paper introduces a novel framework that mainly targets to achieve a computational effective resource management technique. The technique uses the stochastic approach in modelling to design a new traffic management scheme that considers multiple traffic possibilities over VMs along with its switching states. Supported by an analytical modelling approach, the proposed technique offers an efficient placement of virtual machine to the physical server, performs the computation of blocks, and explores reduced resource usage. The study outcome was found to possess potential reduction in live migration, more extent of VM mapping with physical servers, and increased level of capacity.

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Server Resource Dimensioning and Routing of Service Function Chain in NFV Network Architectures

Cited by 38 publications

References 20 publications

An Analytical Cost-Optimal Cloudlet Placement Framework over Fiber-Wireless Networks with Quasi-Convex Latency Constraint

An Analytical Cost-Optimal Cloudlet Placement Framework over Fiber-Wireless Networks with Quasi-Convex Latency Constraint

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

Framework of Resource Management using Server Consolidation to Minimize Live Migration and Load Balancing

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