Impact of Processing Costs on Service Chain Placement in Network Functions Virtualization

The Network Functions Virtualization (NFV) paradigm is the most promising technique to help network providers in the reduction of capital and energy costs. The deployment of virtual network functions (VNFs) running on generic x86 hardware allows higher flexibility than the classical middleboxes approach. NFV also reduces the complexity in the deployment of network services through the concept of service chaining, which defines how multiple VNFs can be chained together to provide a specific service. As a drawback, hosting multiple VNFs in the same hardware can lead to scalability issues, especially in the processing-resource sharing. In this paper, we evaluate the impact of two different types of costs that must be taken into account when multiple chained VNFs share the same processing resources: the upscaling costs and the context switching costs. Upscaling costs are incurred by VNFs multi-core implementations, since they suffer a penalty due to the needs of load balancing among cores. Context switching costs arise when multiple VNFs share the same CPU and thus require the loading/saving of their context. We model through an ILP problem the evaluation of such costs and we show their impact in a VNFs consolidation scenario, when the x86 hardware deployed in the network is minimized

A service-oriented approach for dynamic chaining of virtual network functions over multi-provider software-defined networks

Emerging technologies such as Software-Defined Networks (SDN) and Network Function Virtualization (NFV) promise to address cost reduction and flexibility in network operation while enabling innovative network service delivery models. However, operational network service delivery solutions still need to be developed that actually exploit these technologies, especially at the multi-provider level. Indeed, the implementation of network functions as software running over a virtualized infrastructure and provisioned on a service basis let one envisage an ecosystem of network services that are dynamically and flexibly assembled by orchestrating Virtual Network Functions even across different provider domains, thereby coping with changeable user and service requirements and context conditions. In this paper we propose an approach that adopts Service-Oriented Architecture (SOA) technology-agnostic architectural guidelines in the design of a solution for orchestrating and dynamically chaining Virtual Network Functions. We discuss how SOA, NFV, and SDN may complement each other in realizing dynamic network function chaining through service composition specification, service selection, service delivery, and placement tasks. Then, we describe the architecture of a SOA-inspired NFV orchestrator, which leverages SDN-based network control capabilities to address an effective delivery of elastic chains of Virtual Network Functions. Preliminary results of prototype implementation and testing activities are also presented. The benefits for Network Service Providers are also described that derive from the adaptive network service provisioning in a multi-provider environment through the orchestration of computing and networking services to provide end users with an enhanced service experience

ScienceSDS: A Novel Software Defined Security Framework for Large-scale Data-intensive Science

Experimental science workflows from projects such as Compact Muon Solenoid (CMS) [6] and Laser Interferometer Gravitational Wave Observatory (LIGO) [2] are characterized by data-intensive computational tasks over large datasets transferred over encrypted channels. The Science DMZ [7] approach to network design favors lossless packet forwarding through a separate isolated network over secure lossy forwarding through stateful packet processors (e.g. fire-walls). We propose ScienceSDS, a novel software denied security framework for securely monitoring large-scale science datasets over a software defined networking and network functions virtualization (SDN/NFV) infrastructure