116 research outputs found

    Service Shifting: a Paradigm for Service Resilience in 5G

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    Many real-world services can be provided through multiple virtual network function (VNF) graphs, corresponding, e.g., to high- and low-complexity variants of the service itself. Based on this observation, we extend the concept of service scaling in network orchestration to service shifting, i.e., upgrading or downgrading the VNF graph to use among those implementing the same service. Service shifting can serve multiple goals, from reducing operational costs to reacting to infrastructure problems. Furthermore, it enhances the flexibility of service-level agreements between network operators and third party content providers (“verticals”). In this paper, we introduce and describe the service shifting concept, its benefits, and the associated challenges, with special reference to how service shifting can be integrated within real-world 5G architectures and implementations. We conclude that existing network orchestration frameworks can be easily extended to support service shifting, and its adoption has the potential to make 5G network slices easier for the operators to manage under high-load conditions, while still meeting the verticals’ requirements.This work is supported by the European Commission through the H2020 projects 5G-TRANSFORMER (Project ID 761536) and 5G-GROWTH (Project ID 856709 )

    Service Shifting: a Paradigm for Service Resilience in 5G

    Get PDF
    Many real-world services can be provided through multiple virtual network function (VNF) graphs, corresponding, e.g., to high- and low-complexity variants of the service itself. Based on this observation, we extend the concept of service scaling in network orchestration to service shifting, i.e., upgrading or downgrading the VNF graph to use among those implementing the same service. Service shifting can serve multiple goals, from reducing operational costs to reacting to infrastructure problems. Furthermore, it enhances the flexibility of service-level agreements between network operators and third party content providers (“verticals”). In this paper, we introduce and describe the service shifting concept, its benefits, and the associated challenges, with special reference to how service shifting can be integrated within real-world 5G architectures and implementations. We conclude that existing network orchestration frameworks can be easily extended to support service shifting, and its adoption has the potential to make 5G network slices easier for the operators to manage under high-load conditions, while still meeting the verticals’ requirements

    Optimization-in-the-Loop for Energy-Efficient 5G

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    We consider the problem of energy-efficient network management in 5G systems, where backhaul and fronthaul nodes have both networking and computational capabilities. We devise an optimization model accounting for the main features of 5G backhaul and fronthaul, and jointly solve the problems of (i) node switch on/off, (ii) VNF placement, and (iii) traffic routing. We implement an optimization module within an application on top of an SDN controller and NFV orchestrator, thus enabling swift, high-quality decisions based on current network conditions. Finally, we validate and test our scheme with real-world power consumption, network topology and traffic demand, assessing its performance as well as the relative importance of the main contributions to the total power consumption of the system.This work was supported by the EU project “5G-Crosshaul: The 5G Integrated fronthaul/backhaul” (grant no. 671598) within the H2020 programme

    An Optimization-enhanced MANO for Energy-efficient 5G Networks

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    5G network nodes, fronthaul and backhaul alike, will have both forwarding and computational capabilities. This makes energy-efficient network management more challenging, as decisions such as activating or deactivating a node impact on both the ability of the network to route traffic and the amount of processing it can perform. To this end, we formulate an optimization problem accounting for the main features of 5G nodes and the traffic they serve, allowing joint decisions about (i) the nodes to activate, (ii) the network functions they run, and (iii) the traffic routing. Our optimization module is integrated within the management and orchestration framework of 5G, thus enabling swift and high-quality decisions. We test our scheme with both a real-world testbed based on OpenStack and OpenDaylight, and a large-scale emulated network whose topology and traffic come from a real-world mobile operator, finding it to consistently outperform state-of-the art alternatives and closely match the optimum

    Energy-efficient Traffic Allocation in SDN-based Backhaul Networks: Theory and Implementation

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    5G networks are expected to be highly energy efficient, with a 10 times lower consumption than today’s systems. An effective way to achieve such a goal is to act on the backhaul network by controlling the nodes operational state and the allocation of traffic flows. To this end, in this paper we formulate energy-efficient flow routing on the backhaul network as an optimization problem. In light of its complexity, which impairs the solution in large-scale scenarios, we then propose a heuristic approach. Our scheme, named EMMA, aims to both turn off idle nodes and concentrate traffic on the smallest possible set of links, which in its turn increases the number of idle nodes. We implement EMMA on top of ONOS and derive experimental results by emulating the network through Mininet. Our results show that EMMA provides excellent energy saving performance, which closely approaches the optimum. In larger network scenarios, the gain in energy consumption that EMMA provides with respect to the simple benchmark where all nodes are active, is extremely high under medium-low traffic load

    A method for semi-field rearing of Varroa destructor (Acari: Varroidae) to obtain mites of controlled age and specific life cycle

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    Varroa destructor is one of the most devastating ectoparasites of the honey bee, Apis mellifera, worldwide. Given that V. destructor has very low survivability and exhibits no successful reproduction away from their natural environment and host and that the availability of mites for experimental purposes is limited by seasonality, several protocols of mite rearing under laboratory conditions have been developed. However, only one of these rearing systems has been able to yield a fertile second generation with a low mite survival. The aim of this study was to develop a semi-field rearing method to obtain mites of known age and life cycle that can be maintained through several generations. We registered and compared survival and reproductive parameters of mites of controlled age during four generations (P, F1, F2, F3) and evidenced no significant differences between these mite groups for these life-history traits. With present results we demonstrate that it is possible to successfully produce a third generation of mites under semi-field conditions. This study brings useful information about key conditions for the proper reproduction of mites in a controlled rearing system and provides a potential standardized method for V. destructor research, especially for host-parasite interaction experiments.Fil: Muntaabski, Irina. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigacion En Ciencias Veterinarias y Agronomicas. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Pque. Centenario. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo.; ArgentinaFil: Russo, Romina Maria. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigacion En Ciencias Veterinarias y Agronomicas. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Pque. Centenario. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo.; ArgentinaFil: Liendo, MarĂ­a Clara. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigacion En Ciencias Veterinarias y Agronomicas. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Pque. Centenario. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo.; ArgentinaFil: Landi, Lucas. Instituto Nacional de TecnologĂ­a Agropecuaria. Centro de InvestigaciĂłn de Recursos Naturales. Instituto de Recursos BiolĂłgicos; ArgentinaFil: Lanzavecchia, Silvia Beatriz. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigacion En Ciencias Veterinarias y Agronomicas. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Pque. Centenario. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo.; ArgentinaFil: Scannapieco, Alejandra Carla. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigacion En Ciencias Veterinarias y Agronomicas. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Pque. Centenario. Instituto de Agrobiotecnologia y Biologia Molecular. Grupo Vinculado Instituto de Genetica "ewald A. Favret" Al Iabimo.; Argentin

    Network Slices for Vertical Industries

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    Network Slicing allows to simultaneously support the specific needs of vertical industries with a diverse range of networking and computing requirements. Network Functions Virtualization (NFV) has been defined to deploy multiple network services on a common infrastructure. We extend the NFV concept to vertical services, i.e. services implemented on top of network services and providing the applications of the verticals. We present a component of the 5G-Transformer system, named vertical slicer, which acts as the interface to verticals. The vertical slicer has two main functionalities: allowing verticals to define vertical services based on a set of service blueprints and arbitrating among several vertical services in case of resource shortage.This work has been partially funded by the EU H2020 5G-Transformer Project (grant no. 761536

    Automated service provisioning and hierarchical SLA management in 5G systems

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    Empowered by network softwarization, 5G systems have become the key enabler to foster the digital transformation of the vertical industries by expanding the scope of traditional mobile networks and enriching the network service offerings. To make this a reality, we propose an automation solution for vertical services provisioning and hierarchical Service Level Agreement (SLA) management. Service scaling is one of the most essential operations to adapt the service deployments and resource allocations to ensure SLA fulfilment. Three different scaling levels are addressed in this work: application-, service- and resource-level. We have implemented our solution in a proof-of-concept of a virtualized mobile network platform, spanning over three geographically-distributed sites. To evaluate our solution, we leverage field tests, focusing on automotive vertical services comprising a mission-critical application (collision-avoidance) and an entertainment one (video streaming). The results demonstrate the excellent performance of our solution, and its ability to automatically deploy vertical services and ensure their SLAs through different levels of service scaling.This work has been partially supported by European Commission H2020 5GPPP through the 5G-TRANSFORMER and 5GROWTH projects (Grants No. 761536 and 856709)
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