Performance evaluation and tuning of Virtual Infrastructure Managers for (Micro) Virtual Network Functions

Ventre, Pier Luigi; Pisa, Claudio; Siracusano, Giuseppe; Schmidt, Florian; Lungaroni, Paolo; Bléfari-Melazzi, Nicola

doi:10.1109/nfv-sdn.2016.7919489

Cited by 12 publications

(14 citation statements)

References 7 publications

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“…Potdar et al [26] evaluated the performance of Docker containers and VMs using standard benchmark tools, such as Sysbench, Phoronix, and Apache benchmark, in terms of CPU performance, memory throughput, storage read/write performance, load test, and operation speed measurement. Ventre et al [27] investigated the performance of the instantiation process of micro-virtualized network functions for open-source virtual infrastructure managers, such as OpenStack Nova and Nomad, on the Xen virtualization platform. The source codes of virtual infrastructure managers were modified to reduce instantiation times.…”

Section: Introductionmentioning

confidence: 99%

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

2021

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The pervasive use of cloud computing has led to many concerns, such as performance challenges in communication- and computation-intensive services on virtual cloud resources. Most evaluations of the infrastructural overhead are based on standard benchmarks. Therefore, the impact of communication issues and infrastructure services on the performance of parallel MPI-based computations remains unclear. This paper presents the performance analysis of communication- and computation-intensive software based on the discrete element method, which is deployed as a service (SaaS) on the OpenStack cloud. The performance measured on KVM-based virtual machines and Docker containers of the OpenStack cloud is compared with that obtained by using native hardware. The improved mapping of computations to multicore resources reduced the internode MPI communication by 34.4% and increased the parallel efficiency from 0.67 to 0.78, which shows the importance of communication issues. Increasing the number of parallel processes, the overhead of the cloud infrastructure increased to 13.7% and 11.2% of the software execution time on native hardware in the case of the Docker containers and KVM-based virtual machines of the OpenStack cloud, respectively. The observed overhead was mainly caused by OpenStack service processes that increased the load imbalance of parallel MPI-based SaaS.

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Section: Introductionmentioning

confidence: 99%

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

2021

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“…However, a deeper analysis (see Section 3 and Section 7) reveals that they do not support Unikernels and that there is room for tailoring the instantiation process to the NFV scenario and to enhance their performance. This work extends [15] and addresses the above question, providing a quantitative analysis of the VIMs under evaluation. Moreover, we release as open source the customized VIMs under analysis complemented with a rich set of tools for their performance evaluation [16], [17].…”

Section: Arxiv:180907701v1 [Csdc] 17 Sep 2018mentioning

confidence: 90%

On the Fly Orchestration of Unikernels: Tuning and Performance Evaluation of Virtual Infrastructure Managers

Ventre

Lungaroni²,

Siracusano

et al. 2021

IEEE Trans. Cloud Comput.

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Network operators are facing significant challenges meeting the demand for more bandwidth, agile infrastructures, innovative services, while keeping costs low. Network Functions Virtualization (NFV) and Cloud Computing are emerging as key trends of 5G network architectures, providing flexibility, fast instantiation times, support of Commercial Off The Shelf hardware and significant cost savings. NFV leverages Cloud Computing principles to move the data-plane network functions from expensive, closed and proprietary hardware to the so-called Virtual Network Functions (VNFs). In this paper we deal with the management of virtual computing resources (Unikernels) for the execution of VNFs. This functionality is performed by the Virtual Infrastructure Manager (VIM) in the NFV MANagement and Orchestration (MANO) reference architecture. We discuss the instantiation process of virtual resources and propose a generic reference model, starting from the analysis of three open source VIMs, namely OpenStack, Nomad and OpenVIM. We improve the aforementioned VIMs introducing the support for special-purpose Unikernels and aiming at reducing the duration of the instantiation process. We evaluate some performance aspects of the VIMs, considering both stock and tuned versions. The VIM extensions and performance evaluation tools are available under a liberal open source licence.

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“…The management and orchestration (MANO) entity in the ETSI architecture maintains catalogs of offered NSs, their SFC compositions, and the available flavors of the VNFs. To manage the two layers, MANO is comprised of three main components: the NFV orchestrator (NFVO [13], the VNF manager (VNFM) [14], and the virtual infrastructure manager (VIM) [15]. These components interact together and with the physical and VNF layers to manage the deployment and lifecycle of the offered NSs, their SFCs, and the physical and virtual resources.…”

Section: Motivationmentioning

confidence: 99%

An Automated VNF Manager based on Parameterized Action MDP and Reinforcement Learning

Samaan

Karmouch

2021

ICC 2021 - IEEE International Conference on Communications

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Managing and orchestrating the behaviour of virtualized Network Functions (VNFs) remains a major challenge due to their heterogeneity and the ever increasing resource demands of the served flows. In this thesis, we propose a novel VNF manager (VNFM) that employs a parameterized actions-based reinforcement learning mechanism to simultaneously decide on the optimal VNF management action (e.g., migration, scaling, termination or rebooting) and the action's corresponding configuration parameters (e.g., migration location or amount of resources needed for scaling ). More precisely, we first propose a novel parameterized-action Markov decision process (PAMDP) model to accurately describe each VNF, instances of its components and their communication as well as the set of permissible management actions by the VNFM and the rewards of realizing these actions. The use of parameterized actions allows us to rigorously represent the functionalities of the VNFM in order perform various Lifecycle management (LCM) operations on the VNFs. Next, we propose a two-stage reinforcement learning (RL) scheme that alternates between learning an action-value function for the discrete LCM actions and updating the actions parameters selection policy. In contrast to existing machine learning schemes, the proposed work uniquely provides a holistic management platform the unifies individual efforts targeting individual LCM functions such as VNF placement and scaling. Performance evaluation results demonstrate the efficiency of the proposed VNFM in maintaining the required performance level of the VNF while optimizing its resource configurations. xii VM Virtual Machine

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Performance evaluation and tuning of Virtual Infrastructure Managers for (Micro) Virtual Network Functions

Cited by 12 publications

References 7 publications

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

On the Fly Orchestration of Unikernels: Tuning and Performance Evaluation of Virtual Infrastructure Managers

An Automated VNF Manager based on Parameterized Action MDP and Reinforcement Learning

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