An analytical tool for performance evaluation of software defined networking services

Lombardo, Alfio; Manzalini, Antonio; Riccobene, Vincenzo; Schembra, Giovanni

doi:10.1109/noms.2014.6838416

Cited by 31 publications

(21 citation statements)

References 2 publications

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“…This processing delay can be assumed as fixed [26] provided that the servers have enough capacity to execute the VNFs, or it can be proportional to the server utilization [12,27]. Thus, both processing and propagation delays should be taken into consideration when the objective is to minimize the delay during the VNF placement [28][29][30]. Attention should be drawn to the fact that the processing delay also includes a queueing delay that is highly affected by the number of users/IoT devices associated with each SC and their traffic rate [1].…”

Section: Related Workmentioning

confidence: 99%

VNF Placement Optimization at the Edge and Cloud †

et al. 2019

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Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers' goal of low deployment costs.

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Section: Related Workmentioning

confidence: 99%

VNF Placement Optimization at the Edge and Cloud †

et al. 2019

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“…1. It follows the NetFATE (Network Function at the Edge) approach [12], that proposes to put virtual network functions at the edge of the network.…”

Section: System Descriptionmentioning

confidence: 99%

“…Related to this matter, there is the need of considering different aspects to allocate resources and optimize the position of virtual network functions [10]. In fact, this has to be decided not only accounting the increased load in the host node, but also the increment of traffic in the portion of network neighboring the node, and the latency caused to the flows that are forced to pass through the node that hosts the required VNF [11][12].…”

Section: Introductionmentioning

confidence: 99%

An Analytical Model to Design and Manage a Green SDN/NFV CPE Node

Faraci

Schembra

2015

IEEE Trans. Netw. Serv. Manage.

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In the last few years SDN and NFV have been introduced with the potential to change the ossified Internet paradigm, with the final goal of creating a more agile and flexible network, at the same time reducing both CAPEX and OPEX costs. For this reason, a lot of research efforts have been devoted to optimize the implementation of these technologies, also inheriting experience from data center management. However, orchestration and management of SDN/NFV nodes present new challenges in respect of data center management, mainly due to the telecommunications context where NFV resides. With this in mind, the target of this paper is to define a management model for NFV customers and service providers, a green policy of the Customer Premises Equipment (CPE) nodes, and an analytical model to support their design. The model is then applied to a case study to demonstrate how it can be used to optimize system performance and choose the most important parameters characterizing the design of a CPE node.

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“…However, these works do not address the problem of assigning paths to the incoming traffic flow requests in order to connect nodes running virtual functions, distinguishing different types of datacenters, as this work actually does. A similar problem has been discussed in [12], whose main contribution is an analytical tool for evaluating the performance of a network populated by micro and cloud datacenters which includes also a model for routing traffic flows across nodes providing network functions. However, they deal with a different optimization problem (the minimization of the total link occupation bandwidth) and do not handle ordered sequences of functions as this work actually does.…”

Section: Introductionmentioning

confidence: 99%

Latency-aware composition of Virtual Functions in 5G

Martini

Paganelli

Cappanera

et al. 2015

Proceedings of the 2015 1st IEEE Conference on Network Softwarization (NetSoft)

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The adoption of the virtualization paradigm in both computing and networking domains portends a landscape of heterogeneous service capabilities and resources pervasively distributed and interconnected and deeply integrated through the 5G network infrastructure. In this service ecosystem, dynamic service demand can be flexibly and elastically accomplished by composing heterogeneous services provisioned over a distributed and virtualized resource infrastructure. Indeed, with the term Virtual Functions we refer to virtual computing as well as network service capabilities (e.g., routers and middlebox functions provided as Virtual Network Functions). In order to cope with the increasingly resource intensive demand, these virtual functions will be deployed in distributed clusters of small-scale datacenters typically located in current exchanges at the network edge and will supplement those deployed in traditional large cloud datacenters. In this work we formulate the problem of composing, computing and networking Virtual Functions to select those nodes along the path that minimizes the overall latency (i.e. network and processing latency) in the above mentioned scenario. The optimization problem is formulated as a Resource Constrained Shortest Path problem on an auxiliary layered graph accordingly defined. The layered structure of the graph ensures that the order of VFs specified in the request is preserved. Additional constraints can be also taken into account in the graph construction phase. Finally, we provide a use case preliminary evaluation of the proposed model.

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An analytical tool for performance evaluation of software defined networking services

Cited by 31 publications

References 2 publications

VNF Placement Optimization at the Edge and Cloud †

VNF Placement Optimization at the Edge and Cloud †

An Analytical Model to Design and Manage a Green SDN/NFV CPE Node

Latency-aware composition of Virtual Functions in 5G

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