orchestrating softwarized networks with a marketplace approach

Abstract In the last years, network softwarization is gaining increasing popularity since it allows to achieve dinamicity and flexibility in network management, stimulating a lot of interest by both academia and industry. Cloud computing paradigm together with the new networking paradigms of Software Defined Networking (SDN) and Network Function Virtualization (NFV) are supporting this evolution, by providing network services as single Virtual Network Functions (VNFs) or chains of them. The main problem is scalability of both infrastructure and management. In fact, in order to support the SDN/NFV paradigm, the Telco Operator should deploy huge data centers, which have to be geographically distributed to guarantee low latencies to time-constrained flows, and implement complex orchestration policies. To this purpose, this paper proposes to extend the SDN/NFV framework with a marketplace where Telco Operator customers behave as third-party sellers with their hardware and software resources providing VNF as a service (VNFaaS), so helping the Telco Operator in providing network services in an efficient and scalable way

Multi-Provider Service Chain Embedding With Nestor

Network function (NF) virtualization decouples NFs from the underlying middlebox hardware and promotes their deployment on virtualized network infrastructures. This essentially paves the way for the migration of NFs into clouds (i.e., NF-as-a-Service), achieving a drastic reduction of middlebox investment and operational costs for enterprises. In this context, service chains (expressing middlebox policies in the enterprise network) should be mapped onto datacenter networks, ensuring correctness, resource efficiency, as well as compliance with the provider's policy. The network service embedding (NSE) problem is further exacerbated by two challenging aspects: 1) traffic scaling caused by certain NFs (e.g., caches and WAN optimizers) and 2) NF location dependencies. Traffic scaling requires resource reservations different from the ones specified in the service chain, whereas NF location dependencies, in conjunction with the limited geographic footprint of NF providers (NFPs), raise the need for NSE across multiple NFPs. In this paper, we present a holistic solution to the multi-provider NSE problem. We decompose NSE into: 1) NF-graph partitioning performed by a centralized coordinator and 2) NF-subgraph mapping onto datacenter networks. We present linear programming formulations to derive near-optimal solutions for both problems. We address the challenging aspect of traffic scaling by introducing a new service model that supports demand transformations. We also define topology abstractions for NF-graph partitioning. Furthermore, we discuss the steps required to embed service chains across multiple NFPs, using our NSE orchestrator (Nestor). We perform an evaluation study of multi-provider NSE with emphasis on NF-graph partitioning optimizations tailored to the client and NFPs. Our evaluation results further uncover significant savings in terms of service cost and resource consumption due to the demand transformations. © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works..EU/FP7/T-NOVA/619520DFG/Collaborative Research Center/1053 (MAKI)EU/FP7/T-NOVADFG/CRC/105

A dynamic pricing algorithm for a network of virtual resources

A service chain is a combination of network services (e.g. network address translation (NAT), a firewall, etc.) that are interconnected to support an application (e.g. video-on-demand). Building a service chain requires a set of specialized hardware devices each of which need to be configured with their own command syntax. By moving management functions out of forwarding hardware into controller software, software-defined networking (SDN) simplifies provisioning and reconfiguration of service chains. By moving the network functions out of dedicated hardware devices into software running on standard x86 servers, network function virtualization (NFV) turns the deployment of a service chain into a more (cost)-efficient and flexible process. In an SDN/NFV-based architecture, those service chains are composed of virtual network functions (VNFs) that need to be mapped to physical network components. In literature, several algorithmic approaches exist to do so efficiently and cost-effectively. However, once mapped, a simple revenue model is used for pricing the requested substrate resources. This often leads to a loss of revenue for the infrastructure provider. In this paper, we propose a more advanced, dynamic pricing algorithm for pricing the requested substrate resources. The proposed algorithm increases the infrastructure provider's revenue based on historic data, current infrastructure utilization levels and the pricing of competitors. Our experimental evaluation shows that the proposed algorithm increases the revenue of the infrastructure provider significantly, independent of the average network utilization.Peer Reviewe

Poster: Don't Interrupt Me When You Reconfigure my Service Function Chains

International audienceNetwork Functions Virtualization (NFV) enablesthe complete decoupling of network functions from proprietaryappliances and runs them as software applications on general–purpose servers. Service Function Chains (SFC) are paths with anordered sequence of network functions that have to be processed.In this paper, we consider the problem of reconfiguring SFCswith the goal of bringing the network from a sub-optimal toan optimal operational state. We propose optimization modelsbased on themake-before-breakmechanism, in which a new SFCis set up before the old one is torn down. Our method takes intoconsideration the chaining requirements of the flows and scaleswell with the number of nodes in the network. We show that,with our approach, the network operational cost defined in termsof both bandwidth and installed network function costs can bereduced and a higher acceptance rate can be achieved