1,836 research outputs found

    Hardware-accelerator aware VNF-chain recovery

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    Hardware-accelerators in Network Function Virtualization (NFV) environments have aided telecommunications companies (telcos) to reduce their expenditures by offloading compute-intensive VNFs to hardware-accelerators. To fully utilize the benefits of hardware-accelerators, VNF-chain recovery models need to be adapted. In this paper, we present an ILP model for optimizing prioritized recovery of VNF-chains in heterogeneous NFV environments following node failures. We also propose an accelerator-aware heuristic for solving prioritized VNF-chain recovery problems of large-size in a reasonable time. Evaluation results show that the performance of heuristic matches with that of ILP in regard to restoration of high and medium priority VNF-chains and a small penalty occurs only for low-priority VNF-chains

    International Conference on Broadband Communications, Networks and Systems

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    Producción CientíficaNetwork Function Virtualization (NFV) is considered to be one of the enabling technologies for 5G. NFV poses several challenges, like deciding the virtual network function (VNF) placement and chaining, and adding backup resources to guarantee the survivability of service chains. In this paper, we propose a genetic algorithm that jointly solves the VNF-placement, chaining and virtual topology design problem in WDM metro ring network, with the additional capacity of providing node protection. The simulation results show how important is to solve all of these subproblems jointly, as well as the benefits of using shared VNF and network resources between backup instances in order to reduce both the service blocking ratio and the number of active CPUs.Ministerio de Economía, Industria y Competitividad (grant TEC2017-84423-C3-1-P)Ministerio de Industria, Comercio y Turismo (grant BES 2015-074514)INTERREG V-A España-Portugal (POCTEP) (grant 0677_DISRUPTIVE_2_E)

    CoShare: An Efficient Approach for Redundancy Allocation in NFV

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    An appealing feature of Network Function Virtualization (NFV) is that in an NFV-based network, a network function (NF) instance may be placed at any node. On the one hand this offers great flexibility in allocation of redundant instances, but on the other hand it makes the allocation a unique and difficult challenge. One particular concern is that there is inherent correlation among nodes due to the structure of the network, thus requiring special care in this allocation. To this aim, our novel approach, called CoShare, is proposed. Firstly, its design takes into consideration the effect of network structural dependency, which might result in the unavailability of nodes of a network after failure of a node. Secondly, to efficiently make use of resources, CoShare proposes the idea of shared reservation, where multiple flows may be allowed to share the same reserved backup capacity at an NF instance. Furthermore, CoShare factors in the heterogeneity in nodes, NF instances and availability requirements of flows in the design. The results from a number of experiments conducted using realistic network topologies show that the integration of structural dependency allows meeting availability requirements for more flows compared to a baseline approach. Specifically, CoShare is able to meet diverse availability requirements in a resource-efficient manner, requiring, e.g., up to 85% in some studied cases, less resource overbuild than the baseline approach that uses the idea of dedicated reservation commonly adopted for redundancy allocation in NFV

    2020 22nd International Conference on Transparent Optical Networks (ICTON)

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    Producción CientíficaNetwork Function Virtualization (NFV) is a promising networking paradigm that will ease the network manageability and increase its flexibility, while reducing costs. In this paradigm, operators must solve the Virtual Network Function (VNF) placement and chaining problems. It is also important to provide backup resources to ensure the survivability of the offered services when a node failure happens. In this paper, we compare two different protection approaches to ensure the service resilience: individual VNF protection and end-to-end protection. Results show the benefits in terms of use of computing resources and energy consumption of protecting each VNF individually, compared to the end-to-end protection approach.Ministerio de Economía, Industria y Competitividad (grant TEC2017-84423-C3-1-P)Ministerio de Industria, Comercio y Turismo (fellowship BES-2015-074514)Research network Go2Edge (grant RED2018-102585-T)Interreg V-A Spain-Portugal (POCTEP) programme 2014- 202

    Genetic algorithm for holistic VNF-mapping and virtual topology design

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    Producción CientíficaNext generation of Internet of Things (IoT) services imposes stringent requirements to the future networks that current ones cannot fulfill. 5G is a technology born to give response to those requirements. However, the deployment of 5G is also accompanied by profound architectural changes in the network, including the introduction of technologies like multi-access edge computing (MEC), software defined networking (SDN), and network function virtualization (NFV). In particular, NFV poses diverse challenges like virtual network function (VNF) placement and chaining, also called VNF-mapping. In this paper, we present an algorithm that solves VNF-placement and chaining in a metro WDM optical network equipped with MEC resources. Therefore, it solves the VNF-mapping in conjunction with the virtual topology design of the underlying optical backhaul network. Moreover, a version of the method providing protection against node failures is also presented. A simulation study is presented to show the importance of designing the three problems jointly, in contrast to other proposals of the literature that do not take the design of the underlying network into consideration when solving that problem. Furthermore, this paper also shows the advantages of using collaboration between MEC nodes to solve the VNF-mapping problem and the advantage of using shared protection schemes. The new algorithm outperforms other proposals in terms of both service blocking ratio, and number of active CPUs (thus reducing energy consumption). Finally, the impact of deploying different physical topologies for the optical backhaul network is also presented.Ministerio de Economía, Industria y Competitividad (grant TEC2017-84423-C3-1-P)Ministerio de Industria, Comercio y Turismo (grant BES 2015-074514)Spanish Thematic Network (contract RED2018-102585-T)INTERREG V-A España-Portugal (POCTEP) program (project 0677_DISRUPTIVE_2_E

    Cloud computing resource scheduling and a survey of its evolutionary approaches

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    A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon
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