Configurable Deployment Descriptor Model in NFV

The integration of software defined networking (SDN) and network function virtualization (NFV) is a promising approach to support flexible service deployment and provisioning. In particular, NFV enables a network service to be represented as one network service function chain, which is composed of several virtual network functions in a specific order. However, with regard to service provisioning in multidomain SDN networks, virtual network functions are deployed in several different SDN domains due to limited resource capacity of each SDN domain. It results in the network service deployment complexity increase and causes additional operating cost. On the other hand, most current network service deployment proposals are limited to static user request scenarios. How to effectively deploy network service across multiple SDN domains to satisfy dynamic service demands of end users is a challenging problem. To address the aforementioned challenge, in this paper, we study the problem of dynamic network service deployment across multiple SDN domains. Specifically, we first design a novel service deployment framework to support dynamic deployment and optimization of virtual network function in multidomain SDN networks. Then, we formulate the problem as a multiobjective optimization problem with the target of jointly minimizing resource consumption cost and operating cost. Furthermore, we transform the multiobjective optimization problem into a single objective optimization model and present an efficient heuristic service deployment approach to solve it by leveraging Dijkstra algorithm. The simulation results demonstrate that the proposed service deployment method is efficient and outperforms comparison methods in terms of service rejection ratio, resource cost, and operating cost.

As a new way to design, deploy and manage networkservices, network functions virtualization (NFV) decouplesthe network functions, from one or more physical networkinfrastructures and black boxes so they can run in software.It therefore comes as no surprise that NFV originated fromservice providers, who were looking to improve the deploymentof new network services to support their revenue and growthobjectives. Within the NFV ecosystem, high availability and lowlatency are one of the key QoS benefits that service providerscan expect from the 5G Cloud and the NFV networks to makedelay-critical services such as remote surgery a reality. Therefore,network services should be placed, chained and routed throughthe network considering users/tenants stringent quality of service(QoS) and service-level agreement (SLA) requirements. To thisend, routing and placement optimization plays a major rolein improving network performance and the overall networkcost. In this paper, we study the problem of virtual networkfunctions (VNFs) placement and routing across the physical hoststo minimize overall latency defined as the queuing delay withinthe edge clouds and in network links. In that respect, this worktakes a holistic view by considering not only VNFs chaining andplacement problem but also considering the flows routing aspectsince these two problems are inter-related and have a majorimpact on network latency.

The integration of software-defined networking (S-DN) and network function virtualization (NFV) is expected to achieve the convenient management and flexible deployment of various sophisticated network functions, and support user applications with guaranteed quality of service (QoS). In this paper, we jointly study route selection and network function placement problem. To stress the service sensitivity on delay, we formulate an optimization problem which minimizes the total end-to-end delay subject to data transmission, service requirement and various available resource constraints. As the formulated problem is an NP-hard problem, which cannot be solved easily, we transform it into three subproblems, i.e., route selection subproblem, network function placement subproblem and resource sharing subproblem of user flows, and solve the three subproblems by applying the K-shortest paths algorithm, Kuhn-Munkres (K-M) algorithm and Lagrangian dual method, respectively. Numerical results demonstrate the effectiveness of the proposed algorithm.

Autonomic communications aim to provide the quality-of-service in networks using self-management mechanisms. It inherits many characteristics from autonomic computing, in particular, when communication systems are running as specialized applications in software-defined networking (SDN) and network function virtualization (NFV)-enabled cloud environments. This paper surveys autonomic computing and communications in the context of software-driven networks, i.e., networks based on SDN/NFV concepts. Autonomic communications create new challenges in terms of security, operations, and business support. We discuss several goals, research challenges, and development issues on self-management mechanisms and architectures in software-driven networks. This paper covers multiple perspectives of autonomic communications in software-driven networks, such as automatic testing, integration, and deployment of network functions. We also focus on self-management and optimization, which make use of machine learning techniques.

Network Function Virtualization (NFV) has promoted the implementation of network functions from expensive hardwares to software middleboxes. These software middleboxes, also called Virtual Network Functions (VNFs), are executed on switch-connected servers. Efficiently deploying such VNFs on servers is challenging because the traffic rate of flows must be fully processed by their requested VNFs when they reach destinations, and the deployed positions of VNFs are restricted by the server capacity. In addition, each network function offers non-uniform VNF models (types) with different configurations of processing volumes and costs. This paper focuses on minimizing the total cost of deploying VNFs for providing a specific network function to all flows in tree-structured networks. First, we prove the NP-hardness of non-uniform VNF deployment in a tree topology and propose a dynamic programming based solution with a pseudo-polynomial time complexity. Then we narrow it down to three simplified cases by focusing on either uniform VNFs or the linear line topology. Specifically, three algorithms are introduced: an improved dynamic programming based algorithm for deploying uniform VNFs in a tree topology, a performance-guaranteed algorithm for deploying non-uniform VNFs in a linear line topology, and an optimal greedy algorithm for deploying uniform VNFs in a linear line topology. Additionally, we generalize our approach to a case of deploying a service chain, which consists of multiple network functions applied to flows in a specific order. We propose two solutions: one is optimal but time-consuming while another is heuristic but efficient. Extensive simulations are conducted to evaluate our algorithms.

Attack-aware Security Function Management

5G networks represent a paradigm shift from their 4G predecessors, engineered to cater to the burgeoning demands of densely populated areas and the high data throughput requirements of the Internet of Things (IoT) and smart city infrastructures. Beyond enhancing fundamental network attributes such as reliability, availability, and security, 5G introduces architectural innovations to accommodate these advanced needs. This paper delves into the architectural nuances of 5G, focusing primarily on the Standalone (SA) deployment method, distinguished by its utilization of network slicing. This approach leverages cutting-edge virtual network technologies, including Software-Defined Networking (SDN) and Network Function Virtualization (NFV), to forge virtual network slices tailored to diverse consumer needs. Such customization is imperative for meeting the expansive and varied connectivity demands characteristic of 5G networks.To navigate the complexities of 5G architecture, this study advocates for the adoption of Reference Architectures (RAs), which provide a high-level abstraction framework for dissecting and understanding intricate systems. By proposing a model that outlines the standalone architecture of 5G networks, our research lays the groundwork for evolving this model into a comprehensive RA for 5G. This foundational work is instrumental in equipping system designers with the tools necessary for generalizing systems to manage design and deployment challenges effectively, as well as the heterogeneity inherent in system components. Additionally, our proposed model facilitates the establishment of a common vocabulary, promoting a coherent understanding of component interactions and offering a unified system perspective. Ultimately, this paper contributes a pivotal model that not only enhances our comprehension of 5G network architecture but also paves the way for future advancements in network design and deployment, promising to significantly impact the development of smart cities and IoT ecosystems.Keywords: 5G, 5G architecture, Reference architecture, patterns. Network slicing, Network Function Virtualization, Virtual Network Function.

Metropolitan networks are undergoing a major technological breakthrough leveraging the capabilities of software-defined networking (SDN) and network function virtualization (NFV). NFV permits the deployment of virtualized network functions (VNFs) on commodity hardware appliances which can be combined with SDN flexibility and programmability of the network infrastructure. SDN/NFV-enabled networks require decision-making in two time scales: short-term online resource allocation and mid-to-long term offline planning. In this paper, we first tackle the dimensioning of SDN/NFV-enabled metropolitan networks paying special attention to the role that latency plays in the capacity planning. We focus on a specific use-case: the metropolitan network that covers the Murcia - Alicante Spanish regions. Then, we propose a latency-aware multilayer service-chain allocation (LA-ML-SCA) algorithm to explore a range of maximum latency requirements and their impact on the resources for dimensioning the metropolitan network. We observe that design costs increase for low latency requirements as more data center facilities need to be spread to get closer to the network edge, reducing the economies of scale on the IT infrastructure. Subsequently, we review our recent joint computation of multi-site VNF placement and multilayer resource allocation in the deployment of a network service in a metro network. Specifically, a set of subroutines contained in LA-ML-SCA are experimentally validated in a network optimization-as-a-service architecture that assists an Open-Source MANO instance, virtual infrastructure managers and WAN controllers in a metro network test-bed.

The discovery process of OPC Unified Architecture (OPC-UA) is well defined but lacks flexibility when implemented in large networks. While the standard provides concepts for local and global discovery services, the core assumption is that all clients and servers are aware of the discovery server(s) in the network. This dependency is a barrier for Plug-and-Play installations and is overcome by self announces via the multicast Domain Name System (mDNS), however, this scales badly with an increasing number of network nodes and deployed servers. We propose a discovery approach based on Software-Defined Networking (SDN) and Network Function Virtualization (NFV), that installs a plug-and-play mechanism for global OPC-UA discovery in modern virtualized networks.

The design, management, and operation of network infrastructure have evolved during the last few years, leveraging on innovative technologies and architectures. With such a huge trend, due to the flexibility and significant economic potential of these technologies, software-defined networking (SDN) and network functions virtualization (NFV) are emerging as the most indispensable key catalysers. SDN/NFV enhancing the infrastructure agility, thus network operators and service providers are able to program their own network functions (e.g., gateways, routers, load balancers) on vendor-independent hardware substrate. One of the most important considerations in NFV deployment is how to allocate the virtual resources that are needed to provide flexible virtual network services in an NFV-based network infrastructure. Thus, the most important prerequisite for NFV deployment is achieved fast, scalable and dynamic composition and allocation of networks functions (NFs) to implement network services (NSs). We have proposed a revised RA algorithm that integrates embedding and scheduling of virtual network functions (VNFs) simultaneously. In this paper, performance evaluation of the revised RA algorithm is performed and the proposed algorithm is applied more effectively in NFV environment where the demand for resources is flexible and concentrated.

Network functions virtualization (NFV) technology is an emerging networking technology in the telecom industry which provides flexible deployment of network services by reducing the Operating Expenses and Capital Expenses. NFV is an innovative step to virtualize network services that usually run on fixed hardware. With the concept of NFV, services like routing, load balancing, deep packet inspectors and firewalls are packaged as virtual network functions (VNFs) on commodity hardware. NFV helps the service provider to flexibly add that service in the form of a virtual machine (VMs) without upgrading or buying a new hardware on the customer end. This allows a faster deployment of the all the network services with new innovations and helps in increasing great opportunities in the field of telecom-networking. This paper provides an information about NFV technology with its characteristics, enabling technologies, benefits, use cases and challenges. NFV architecture and its comparison with Software Defined Networking (SDN) technology is also presented in this survey paper.

Network function virtualization (NFV) decouples network functions (NFs) from dedicated hardware, leading to significant cost reduction in network service provisioning. With NFV, a network service is represented by a series of inter-connected virtual network functions (VNFs), forming a service function chain (SFC). The problem of placing the VNFs on the NFV infrastructure (NFVI) and establishing the routing paths between them, according to the service chain template, is termed as SFC embedding. The objectives and constraints for the optimization problem formulation of SFC embedding may vary depending on the corresponding network service. We introduce the notion of trustworthiness as a measure of security in SFC embedding and thus network service deployment. We formulate the resulting trust-aware SFC embedding problem as a Mixed Integer Linear Program (MILP). We relax the integer constraints to reduce the time complexity of the MILP formulation, and obtain a Linear Program (LP). We investigate the trade-offs among the two formulations, seeking to strike a balance between results accuracy and time complexity.

A virtualized network infrastructure is composed of multiple virtualized network functions (VNF) interconnected by well defined interfaces, and thus forming a VNF-graph. The initial deployment of such a VNF-graph inside a data center (DC) is a complex task with multidimensional aspects compared to deploying a single VNF that may represent a single network function. The problem space becomes more complex when each VNF is further decomposed into multiple VNF components (VNFC), where each VNFC embodies a subset of network functions attributed to the respective VNF. The challenge is to ensure that the deployment strategy meets the intra-functional constraints between the multiple VNFCs constituting the VNF-graph while ensuring service, performance and operational integrity, and also ensures optimal utilization of the underlying resources of the DC infrastructure (DCI). In this article we analyze the cost incurred by two “constraint-based heuristically applied” initial VNF/VNFC deployment strategies with reference to a virtualized mobile network infrastructure providing EPCaaS (evolved packet core as a service) while taking into consideration functional and administrative constraints. The cost of deployment is measured in terms of the utilization of DC infrastructure resources such as compute and networking. We also present the discussion in view of the ETSI NFV MANO framework, undergoing standardization, that is responsible for management and orchestration of NFV systems including VNF deployment.

Recent years have seen a revolution in network infrastructure brought on by the ever-increasing demands for data volume. One promising proposal to emerge from this revolution is Network Functions Virtualization (NFV), which has been widely adopted by service and cloud providers. The essence of NFV is to run network functions as virtualized workloads on commodity Standard High Volume Servers (SHVS), which is the industry standard. However, our experience using NFV when deployed on modern NUMA-based SHVS paints a frustrating picture. Due to the complexity in the NFV data plane and its service function chain feature, modern NFV deployment on SHVS exhibits a unique processing pattern — heterogeneous software pipeline (HSP), in which the NFV traffic flows must be processed by heterogeneous software components sequentially from the NIC to the end re-ceiver. Since the end-to-end performance of flows is cooperatively determined by the performance of each processing stage, the resource allocation/mapping scheme in NUMA-based SHVS must consider a thread-dependence scheduling to tradeoff the impact of co-located contention and remote packet transmission. In this paper, we develop a thread scheduling mechanism that collaboratively places threads of HSP to minimize the end-to-end performance slowdown for NFV traffic flow. It employs a dynamic programming-based method to search for the optimal thread mapping with negligible overhead. To serve this mechanism, we also develop a performance slowdown estimation model to accurately estimate the performance slowdown at each stage of HSP. We implement our collaborative thread scheduling mechanism on a real system and evaluate it using real workloads. On average, our algorithm outperforms state-of-the-art NUMA-aware and contention-aware scheduling policies by at least 7% on CPU utilization and 23% on traffic throughput with negligible computational overhead (less than 1 second).

Fault tolerant placement of stateful VNFs and dynamic fault recovery in cloud networks