Green virtual network embedding with supervised self-organizing map

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.

The main resource allocation research challenge in network virtualization is the Virtual Network Embedding (VNE) Problem. It consists of two stages, usually performed separately: node mapping and link mapping. A new mathematical multi-constraint routing framework for linear and non-linear metrics called “paths algebra” has already been proposed to solve the second stage, providing good results thanks to its flexibility. Unlike existing approaches, paths algebra is able to include any kind of network parameters (linear and non-linear) to solve VNE in reasonable runtime. While paths algebra had only been used to solve one stage (link mapping) of the VNE, this paper suggests an improvement to solve VNE using the paths algebra-based strategy by coordinating, in a single stage, the mapping of nodes and links based on a ranking made of the bi-directional pair of nodes of the substrate network, ordered by their available resources. Simulation results show that the New Paths Algebra-based strategy shows significant performance improvements when compared against the uncoordinated paths Algebra-based link mapping approach.

This paper explores the most urgent task to initialize a virtual network in the network virtualization environment, which always called the virtual network embedding. Different to the previous works to take the embedding process as two steps: node mapping stage and then edge mapping stage, this paper contribute to solve these processes all in one discrete nonlinear combined optimization. Based on modeling the virtual network (VN) request and substrate network (SN), this paper proposed mathematical description to the embedding process which building the relationship between node mapping and edge mapping stages. After that, a virtual network embedding cost is introduced as an objective function, and then the virtual network embedding can be concluding to minimize the objective cost as a mathematical programming problem. The obtained programming results in LINGO9.0 show that the proposed method can finish a virtual network embedding by mathematical programming in one step.

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.

We propose a novel dynamic transparent virtual network embedding (VNE) algorithm, which considers node mapping and link mapping jointly, for network virtualization over optical orthogonal frequency-division multiplexing (O-OFDM) based elastic optical infrastructures. For each virtual optical network (VON) request, the algorithm first transfers the substrate optical network into a layered-auxiliary-graph according to the spectrum usage of each fiber link, then applies a node mapping approach that considers the local information of all substrate nodes, and accomplishes the link mapping, in a single layer of the auxiliary graph. The simulation results verify that the proposed algorithm considers the uniqueness of O-OFDM networks and outperforms two reference algorithms that directly apply the VNE schemes developed for Layer 2/3 or WDM network virtualization, by providing lower VON blocking probability. The simulations with a realistic topology also demonstrate that the average lengths of embedded substrate paths are well-controlled within the typical transmission reaches of O-OFDM signals. To the best of our knowledge, this is the first proposal that includes both link mapping and node mapping to address dynamic transparent VNE over elastic optical infrastructures.

Network virtualization (NV) provides a feasible mechanism for operating numerous diverse virtual networks concurrently on a shared physical infrastructure network. The key issue in NV is virtual network embedding (VNE), which efficiently and effectively maps virtualized networks (VNs) with multiple resource needs for nodes and links to the underlying physical network with limited resources. A multiple topological attributes (MTA) based embedding algorithm is proposed to address the issue of providing different virtual request ser-vices delivered in a wireless network environment, leading to an unstable utilization of physical network resources and a low access rate for subsequent requests. It is emphasized that machine learning (ML) should be integrated into the process of network slicing in order to properly classify the received wireless virtual request. In this work, virtual request services are categorized automatically using support vector machine (SVM), and resources are allocated accordingly. The proposed technique organizes nodes in the embedding process according to their priority based on multiple topological properties of virtual and physical networks. According to the findings of the simulations, the SVM-MTA algorithm enhances both the acceptance rate and the resource efficiency of the network.

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.

A hybrid optical/electrical datacenter network (HOE-DCN) integrates the benefits of electrical packet switching (EPS) and optical circuit switching (OCS) for better architectural scalability. Meanwhile, as each network service usually involves multiple virtual machines (VMs) that form a virtual network (VNT), how to reconfigure the VNTs in an HOE-DCN to adapt to the dynamic network environment becomes an interesting and important problem to tackle. In this work, we optimize the procedure of VNT reconfigurations that remap VNTs to given virtual network embedding (VNE) schemes, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , scheduling the required VM migrations and optical cross-connect (OXC) reconfiguration properly such that the overall VNT reconfiguration latency can be minimized. We first assume that all the VM migrations should be scheduled before the OXC reconfiguration to minimize service interruptions, and formulate a mixed integer linear programming (MILP) model to solve the scheduling problem exactly. Then, with the same assumption, we propose a time-efficient heuristic to schedule parallel VM migrations in batches such that the bandwidth competition can be significantly relieved. Finally, we divide the OXC reconfiguration into several progressive steps, and design a joint scheduling algorithm to arrange VM migrations together with the OXC reconfiguration steps.

Network virtualization (NV) has widely envisioned as a crucial factor for the success of the future networks by enabling a flexible, cost-effective and on-demand deployments of multiple network service requests on a shared physical infrastructure. The major challenge of NV is to efficiently and effectively embed heterogeneous virtual network requests (VNRs), consisting of a set of virtual nodes connected by virtual links, onto a shared substrate network meeting various stringent resource constraints. Most of the research papers in this field have merely focused on separate virtual node mapping (VNoM) or virtual link mapping (VLiM) with scalable heuristic algorithms. The lack of a coordination between node and link mapping stages results in low acceptance ratio as well as network revenues. In this paper, we propose a new approach based on Genetic Algorithm (GA) that jointly coordinates node and link mappings where the link mapping is relied on a path ranking method. A novel heuristic conciliation mechanism is introduced to handle a possible set of infeasible link mappings during gener-ating virtual embedding solutions in GA&#x0027;s operations. Extensive evaluation results show that our proposed GA-based algorithm outperforms state-of-the-art virtual embedding algorithms in all performance metrics we adopted.

Virtual network embedding (VNE), which is a significant problem in cloud computing, has gained much attention among many researchers recently. Due to the NP-hardness of VNE, the existing solvers are either inefficient or inaccurate. This paper develops a novel algorithm based on the ant colony system (ACS). To solve the VNE problem, the algorithm structure concentrates on the link mapping from virtual network to substrate network. Particularly, for a specific virtual network request, we first sort the embedding sequence of virtual nodes according to their link resources. Then, ACS is used to embed the virtual nodes onto substrate nodes according the sorted sequence, while the virtual links are mapped via a shortest path strategy for the embedded nodes. For the first time, we propose a link resource heuristic information and incorporate it into the search process of ACS. The link resource heuristic information has two significant effects, one is to make virtual nodes tend to be embedded on the substrate nodes that cost less bandwidth, and the other is to confirm the connectivity of the substrate nodes that embed the virtual nodes. The proposed algorithm improves the optimization performance of VNE when compared with a few existing algorithms, while it substantially reduces the cost of time.

Network virtualization recognized as an enabling technology for the forthcoming networks is utterly popular. One of the main challenges of network virtualization is called the virtual network embedding problem. Virtual network embedding (VNE) aims to allocate a set of virtual machines onto a set of interconnected physical hardware in the cloud computing environment. Traditional exact solutions, considered as a time-consuming process to achieve a global optimal solution, have been proofed to be $\mathcal{N}\mathcal{P}$-hard. On the other hand, some existing heuristic solutions tend to decouple VNE problems into two stages: virtual node mapping (VNoM) and virtual link mapping (VLiM). Undoubtedly, these kinds of decomposition would result in low acceptance ratio and inefficient substrate resource utilization. In this paper, we propose a distributed parallel Genetic Algorithm combined with graph theory for solving VNE in one-stage. Our proposed algorithm achieves better performance than previous baseline solutions while meeting the stringent time requirements for online VNE problems.

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.

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.

Network virtualization (NV) is one important attribute of the next generation network (e.g, upcoming 5G virtualized networking). Virtual network embedding (VNE) is about the resource allocation problem in NV. Multiple VNE algorithms have been proposed over the past decade. Prior algorithms focus on accepting more virtual networks (VNs) in one shared substrate network (SN) in order to maximize the embedding revenue. As energy cost is approaching half of the SN operating cost, it is crucial for infrastructure providers to minimize energy cost. In addition, in real networking environment, it is vital to embed each VN among multiple SNs, geographically distributed in different regions. To address both issues, we firstly propose the formal VNE problem model and VNE energy cost model. Then an energy efficient heuristic algorithm (EEMD-VNE) is detailed, aiming at maximizing the net profit. Meanwhile, the EEMD-VNE is able to embed each requested VN among multiple SNs in polynomial time. Numerical simulation results reveal that the EEMD-VNE significantly reduces the energy cost by approximately 8.5% over the existing energy related algorithms for accommodating the same amount of VNs.

This paper presents a platform for virtual network (VN) provisioning across multiple domains. The platform decomposes VN provisioning into multiple steps to address the implications of limited information disclosure on resource discovery and allocation. A new VN embedding algorithm with simultaneous node and link mapping allows to assign resources within each domain. For inter-domain virtual link setup, we design and realize a signaling protocol that also integrates resource reservations for providing virtual links with Quality-of-Service guarantees. Experimental results show that small VNs can be provisioned within a few seconds.