A Novel One-stage Distributed Parallel Embedding for Virtualized Network Environment

Network virtualization is widely considered to be one of the main paradigms to solve the Internet ossification problem. One of the most challenging works in this paradigm will be the efficient use of the substrate resources, which is known as virtual network embedding (VNE) problem. The VNE problem is known to be an NP-hard problem which needs some heuristic and approximate algorithms to be solved. In this paper, the VNE is decomposed into two stages: virtual node and virtual link mapping. In the node mapping stage, the breadth first search algorithm is employed to construct loop-free tree for each substrate node, then we explored different hops sufficient capacity of each SN node via the loop-free tree, and analyze the best value of hops that contributes to gain better performance for the algorithm. And the link mapping stage, it can be seen as multi-constraint routing, which is known to be an NP-hard problem. The paths algebra framework was adopted to address this problem, for its convergence for multi-constraint routing problem and a large solution space that the algorithm can gain an enhanced optimization performance.

Aiming at the virtual network embedding problem under dynamic service request, Service Request Aware-based Dynamic Virtual Network Embedding (SRAD) algorithm is proposed. We first present virtual network embedding model, and then define virtual network construction cost according to the dynamic characteristic of service request. Our goal is to find the optimal reconfiguration policies by awaring service request type and changing trends, which can minimize the overall construction cost using substrate resource. Experimental results show that the proposed algorithm satisfies the service request, achieves higher success ratio and gains higher revenue/cost ratio for substrate network comparing with the existing algorithms.

Network virtualization promises a future Internet that inherently supports technological advancement. Extensive literature studies have been devoted to the fundamental problem, namely Virtual Network Embedding (VNE) in network virtualization, which instantiates the virtual network request (VNR) customized by the Service Provider (SP) to the substrate network managed by the Infrastructure Provider (InP). Different from prior studies, in this work, we identify security issues that are associated with the VNE process, which is further incorporated and addressed in the Security-Aware Virtual Network Embedding (SVNE) problem. Our efforts aim to fill the major gaps in the literature studies on the VNE problem: first, we assess the security issues in VNE at node, topology and network levels and explicitly define open, flexible and fine-granular security plans that can address above issues; second, we present and evaluate a comprehensive framework that implements the proposed security plans and address the SVNE problem.

Network virtualization technology makes multiple virtual networks (VNs) that provide heterogeneous services share the same substrate network. Virtual network embedding (VNE) maps VNs to the substrate network, and allocates network resources. In this paper, we provide VNE algorithms for efficient management of flexi-grid networks, where virtual link mapping in flexi-grid networks satisfies continuity and contiguity constraints of the spectrum assignment. We provide a column generation algorithm for the VNE problem. Numerical results show the functionality and the efficiency of the algorithm.

Recently network virtualization has been proposed as a promising way to overcome the current ossification of the Internet by allowing multiple heterogeneous virtual networks (VNs) to coexist on a shared infrastructure. A major challenge in this respect is the VN embedding problem that deals with efficient mapping of virtual nodes and virtual links onto the substrate network resources. Since this problem is known to be NP-hard, previous research focused on designing heuristic-based algorithms which had clear separation between the node mapping and the link mapping phases. This paper proposes VN embedding algorithms with better coordination between the two phases. We formulate the VN embedding problem as a mixed integer program through substrate network augmentation. We then relax the integer constraints to obtain a linear program, and devise two VN embedding algorithms D-ViNE and R-ViNE using deterministic and randomized rounding techniques, respectively. Simulation experiments show that the proposed algorithms increase the acceptance ratio and the revenue while decreasing the cost incurred by the substrate network in the long run.

A novel evaluation function for higher acceptance rates and more profitable metaheuristic-based online virtual network embedding

To solve the energy‐efficient virtual network embedding problem, this study proposes an embedding algorithm based on Hopfield neural network. An energy‐efficient virtual network embedding model was established. Wavelet diffusion was performed to take the structural feature value into consideration and provide a candidate set for virtual network embedding. In addition, the Hopfield network was used in the candidate set to solve the virtual network energy‐efficient embedding problem. The augmented Lagrangian multiplier method was used to transform the energy‐efficient virtual network embedding constraint problem into an unconstrained problem. The resulting unconstrained problem was used as the energy function of the Hopfield network, and the network weight was iteratively trained. The energy‐efficient virtual network embedding scheme was obtained when the energy function was balanced. To prove the effectiveness of the proposed algorithm, we designed two experimental environments, namely, a medium‐sized scenario and a small‐sized scenario. Simulation results show that the proposed algorithm achieved a superior performance and effectively decreased the energy consumption relative to the other methods in both scenarios. Furthermore, the proposed algorithm reduced the number of open nodes and open links leading to a reduction in the overall power consumption of the virtual network embedding process, while ensuring the average acceptance ratio and the average ratio of the revenue and cost.

Artificial algae optimization for Virtual Network Embedding problems in 5G network slicing scenarios

Service-oriented network virtualization enables a Network-as-a-Service paradigm to be available in cloud computing, thereby allowing network infrastructures to be exposed and utilized on demand. Virtual network embedding is a core network virtualization technique; however, a number of conflicting embedding objectives must be accommodated when implementing virtual network embedding. In this paper, we propose a multi-objective virtual network embedding framework to balance various mapping (or embedding) objectives. In addition, we apply an improved multi-objective group search optimizer to solve the virtual network embedding problem and generate trade-off solutions. Experimental results suggest that multi-objective virtual network embedding can balance various mapping objectives while achieving excellent results for acceptance ratios and revenue.

In a network virtualization-enabled software-defined networking (SDN), the problem of virtual network embedding (VNE) is a major concern. Although a number of VNE algorithms have been proposed, they fail to consider the efficient utilization of substrate resources or the network load extensively, thus resulting in less efficient utilization of substrate resources or higher blocking ratio of the virtual networks. In this paper, we study the problem of mapping a number of virtual networks in SDN and formulate the VNE problem as a network load minimization problem. Since the formulated optimization problem is NP-hard and it cannot be solved conveniently, we propose a two-stage VNE algorithm consisting of node mapping stage and link mapping stage. Numerical results demonstrate that the effectiveness of our proposed algorithm.

In the network virtualization environments, one of the most challenges is how to map the virtual networks (VNs) onto a shared substrate network managed by an infrastructure provider (InP), which is termed as virtual network embedding problem. Prior studies on this issue only emphasize on maximizing the revenue or minimizing the energy consumption while ignoring the reliability requirements of end-users. In our work, we incorporate the reliability probability into the virtual network embedding process with an aim to improve the QoS/QoE of end users from a new perspective. We devised two novel reliable virtual network embedding algorithms called RRW-MaxMatch and RDCC-VNE based on RW-MaxMatch and DCC-VNE, respectively. Extensive simulations demonstrated that the efficiency of our proposed algorithms is better than those of two primitive algorithms in terms of the reliability demands, the acceptance ratio of virtual networks and the long-term average revenue.

Network Virtualization offers a solution for Future Internet and it is a key enabler for cloud computing applications. Virtual Network Embedding (VNE) problem deals with resource allocation of a physical infrastructure to Virtual Network Requests (VNRs). Several performance metrics are employed in order to evaluate the efficiency of specific VNE approaches. These existing metrics, mostly related to Infrastructure Provider profit, are computed at the end of the VNE process, after embedding many VNRs. This work proposes a novel performance metric, VNE-NP (VNE Normalized Profit) which combines aspects of the two metrics most used in the literature: Blocking Probability and Embedding Cost.

Efficient network resource utilization is crucial in Virtual Network Embedding (VNE) problem. The diversity of virtual topologies belong to various services providers (SPs) severely affects the efficiency of VNE algorithms and fairness between SPs. This paper proposes a fair VNE algorithm with a topological transformation mechanism. Such mechanism will transform virtual topology to reduce complexity. Then the algorithm will felicitously map the virtual network onto substrate network through a Disperse Particle Swarm Optimization (DPSO) based process. Simulation results show that due to the topological transformation procedure the algorithm can achieve more fairness than traditional VNE algorithms.

The Virtual Network Embedding Problem (VNEP) captures the essence of many resource allocation problems. In the VNEP, customers request resources in the form of Virtual Networks. An embedding of a virtual network on a shared physical infrastructure is the joint mapping of (virtual) nodes to physical servers together with the mapping of (virtual) edges onto paths in the physical network connecting the respective servers. This work initiates the study of approximation algorithms for the VNEP for general request graphs. Concretely, we study the offline setting with admission control: given multiple requests, the task is to embed the most profitable subset while not exceeding resource capacities. Our approximation is based on the randomized rounding of Linear Programming (LP) solutions. Interestingly, we uncover that the standard LP formulation for the VNEP exhibits an inherent structural deficit when considering general virtual network topologies: its solutions cannot be decomposed into valid embeddings. In turn, focusing on the class of cactus request graphs, we devise a novel LP formulation, whose solutions can be decomposed. Proving performance guarantees of our rounding scheme, we obtain the first approximation algorithm for the VNEP in the resource augmentation model. We propose different types of rounding heuristics and evaluate their performance in an extensive computational study. Our results indicate that good solutions can be achieved even without resource augmentations. Specifically, heuristical rounding achieves 77.2% of the baseline’s profit on average while respecting capacities.

QoS satisfaction aware and network reconfiguration enabled resource allocation for virtual network embedding in Fiber-Wireless access network