A Security-oriented Dynamic and Heterogeneous Scheduling Method for Virtual Network Function

Network Function Virtualization (NFV) is a paradigm that virtualizes traditional network functions and instantiates Virtual Network Functions (VNFs) as software instances separate from hardware appliances. Service Chaining (SC), seen as one of the major NFV use cases, provides customized services to users by concatenating VNFs. A VNF placement model for SC that relaxes the visit order constraints of requested VNFs has been considered. Relaxing the VNF visit order constraints reduces the number of VNFs which need to be placed in the network. However, since the model does not permit any loop within an SC path, the efficiency of utilization of computation resources deteriorates in some topologies. This paper proposes a VNF placement model for SC which minimizes the cost for placing VNFs and utilizing link capacity while allowing both relaxation of VNF visit order constraints and configuration of SC paths including loops. The proposed model determines routes of requested SC paths, which can have loops, by introducing a logical layered network generated from an original physical network. This model is formulated as an Integer Linear Programming (ILP) problem. A heuristic algorithm is introduced for the case that the ILP problem is not tractable. Simulation results show that the proposed model provides SC paths with smaller cost compared to the conventional model.

Diverse proprietary network appliances increase both the capital and operational expense of service providers, meanwhile causing problems of network ossification. Network function virtualization (NFV) is proposed to address these issues by implementing network functions as pure software on commodity and general hardware. NFV allows flexible provisioning, deployment, and centralized management of virtual network functions. Integrated with SDN, the software-defined NFV architecture further offers agile traffic steering and joint optimization of network functions and resources. This architecture benefits a wide range of applications (e.g., service chaining) and is becoming the dominant form of NFV. In this survey, we present a thorough investigation of the development of NFV under the software-defined NFV architecture, with an emphasis on service chaining as its application. We first introduce the software-defined NFV architecture as the state of the art of NFV and present relationships between NFV and SDN. Then, we provide a historic view of the involvement from middlebox to NFV. Finally, we introduce significant challenges and relevant solutions of NFV, and discuss its future research directions by different application domains.

VNF Performance modelling: From stand-alone to chained topologies

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.

Network function virtualization (NFV) decouples software implementations of network functions from their hosts (or hardware). NFV exposes a new set of entities, the virtualized network functions (VNFs). The VNFs can be chained with other VNFs and physical network functions to realize network services. This flexibility introduced by NFV allows service providers to respond in an agile manner to variable service demands and changing business goals. In this context, the efficient establishment of service chains and their placement becomes essential to reduce capital and operational expenses and gain in service agility. This paper addresses the placement aspect of these service chains by finding the best locations and hosts for the VNFs and to steer traffic across these functions while respecting user requirements and maximizing provider revenue. We propose a novel eigendecomposition-based approach for the placement of virtual and physical network function chains in networks and cloud environments. A heuristic based on a custom greedy algorithm is also presented to compare performance and assess the capability of the eigendecomposition approach. The performance of both algorithms is compared to a multi-stage-based method from the state of the art that also addresses the chaining of network services. Performance evaluation results show that our matrix-based method, eigendecomposition of adjacency matrices, has reduced complexity and convergence times that essentially depend only on the physical graph sizes. Our proposal also outperforms the related work in provider’s revenue and acceptance rate.

Network Function Virtualization (NFV) is an emerging technology decouples network functions from hardware. Network service in NFV is deployed as a service chain, also known as Service Function Chain (SFC). SFC consists of an ordered set of Virtual Network Functions (VNFs). However, VNFs bring new challenges in providing network services with availability guarantee. In addition, in a customizable and dynamic NFV-enabled network, the composition and mapping of service chain are different from that of a traditional network. In this paper, we define an availability model that takes both hardware and VNF failures into consideration. Then we propose Joint Path-VNF backup model to combine path and VNF backup in a joint way. And a priority-based algorithm is designed for service chain composition and mapping. Simulation results show that our proposed solutions can reduce resource consumption while guaranteeing availability.

Attack-aware Security Function Management

By using Network Function Virtualization (NFV), several kinds of network functions can be provided in commercial off-the-shelf (COTS) servers. Such network function is called Virtual Network Function (VNF). In terms of the utilization of VNFs, an emerging technology called service chaining enables network operators to provide network services dynamically and flexibly. Here, the number of VNF instances should be managed dynamically according to the amount of traffic. In this paper, we propose a dynamic management of VNF instances with Model Predictive Control (MPC) for multiple service chains. In the proposed method, the number of VNF instances is changed dynamically according to the predicted amount of traffic. We evaluate the performance of the proposed method and threshold method with simulation. In numerical examples, it is shown that the proposed method can avoid data loss with a small number of VNF instances.

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.

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 rapid development of network function virtualization (NFV) enables a communication network to provide in-network services using virtual network functions (VNFs) deployed on general IT hardware. While existing studies on NFV focused on how to provision VNFs from the provider's perspective, little is done about how to validate the provisioned resources from the user's perspective. In this work, we take a first step towards this problem by developing an inference framework designed to “look into” the NFV network. Our framework infers the structure and state of the overlay formed by VNF instances, ingress/egress points of measurement flows, and critical points on their paths (branching/joining points). Our solution only uses external observations such as the required service chains and the end-to-end performance measurements. Besides the novel application scenario, our work also fundamentally advances the state of the art on topology inference by considering (i) general topologies with general measurement paths, and (ii) information of service chains. Our evaluations show that the proposed solution significantly improves both the reconstruction accuracy and the inference accuracy over existing solutions, and service chain information is critical in revealing the structure of the underlying topology.

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.

Software-Defined Networking (SDN) provides the capability to steer traffic in a network to lower the management cost. Network Function Virtualization (NFV) gives the chance to implement network functions at the right time and the right place to increase operation flexibility. Together SDN and NFV show the potential to create an agile system with a low operations cost and a high customer satisfaction. However, the combination of SDN with NFV results in the redundant packet forwarding traffic inside SDN in order to forward packets based on the deployed network functions for a service chain. Besides, it also increase the computation requirement of a controller for possible packet header modifications and flow states management. In this paper, we propose to implement network functions on SDN switches to lower the traffic inside of SDN and the computation requirement of a SDN controller. We create network function modules for open virtual switches and make those functions to be managed by a controller with an algorithm to streamline the implemented service chains. Our results show that the proposed system can reduce about 2/3 of current network traffic compared to the current solutions without the modification of forwarding tables and packets.

Network Function Virtualization (NFV) is a promising approach for providing efficient and flexible network functions deployment, which also reduces the cost in the network operations compared to traditional method using dedicated hardware. Multiple virtual network functions can be chained together working as service chain to provide a specific service. When multiple network functions share computing resources, how to efficiently schedule them dynamically is a great challenge. In this paper, we first investigate the issue that a single packet drop occurs at different positions of a service chain may have different impact on the performance. In light of this, a packets dropping cost model is carefully defined based on the NF positions in a service chain. Then, according to linear programming, a Minimizing Dropping Cost (MDC) approach is proposed to optimally schedule vNFs. Simulation results show that the proposed algorithm can reduce the total incurred cost by up to 60% compared to the existing common schedule approach.

Using Network Functions Virtualization (NFV), network functions are virtualized and chained together to provide a network service. Often, a service chain can be allocated in multiple different ways, making use of different physical or virtual network functions, resulting in varying quality of service and deployment costs. In this paper, we introduce customizable function chains, which model the services within a service chain and their variability, and present a management framework that can be used to deploy these services, making it possible to take service chain variability into account at runtime. We present and evaluate a model for resource allocation of network functions within NFV environments, focusing on a hybrid scenario where part of the network functions may be provided by dedicated physical hardware, and where part of the functions are provided using virtualized instances. We numerically study our approach using a small network provider scenario, on which a connectivity service is deployed, and analyze the benefit of the approach. In our evaluations, we find this approach results in a lower cost compared to an approach which does not support variability, both due to a reduction in the server use cost, and a reduction in failure cost when insufficient resources are present.