Network Embedding Algorithm Research Articles

Mobility Aware Virtual Network Embedding

Over the last years, network virtualization has become one of the most promising solutions for sustainability towards the ongoing increase of data demand in mobile networks. Within that context, the virtual network embedding problem has recently been studied extensively and many different solutions have been proposed; but, mainly these studies have focused on wired networks. The main purpose of this paper is to provide an optimization framework for optimal virtual network embedding, including a heuristic algorithm with low computational complexity, by explicitly considering the effect of supporting the actual user mobility, assuming the emerging Distributed Mobility Management (DMM) scheme as well as a traditional Centralized Mobility Management (CMM) scheme. In addition to that, service differentiation is introduced, giving higher priority to time-critical over-the-top (OTT) services compared to more traditional elastic Internet applications. The performance of the proposed framework is compared to mobility agnostic greedy algorithms as well as virtual network embedding algorithms from the literature. Numerical investigations reveal that the effect of user mobility has a significant impact on the design of virtual networks. Additionally, the mobility aware scheme can provide tangible gains in the overall performance compared with the previous proposed schemes that do not take explicitly into account the effect of user mobility.

A proposal of survivable virtual network embedding algorithm

A proposal of survivable virtual network embedding algorithm

Efficient Virtual Network Embedding With Backtrack Avoidance for Dynamic Wireless Networks

We develop an efficient virtual network embedding (VNE) algorithm, termed B ird -VNE, for mobile wireless networks. B ird -VNE is an approximation algorithm that ensures a close to optimal virtual embedding profit and acceptance rate while minimizing the number of virtual network migrations resulting from the mobility of wireless nodes. B ird -VNE employs a constraint satisfaction framework by which we analyze the constraint propagation properties of the VNE problem and design constraint processing algorithms that efficiently narrow the solution space and avoid backtracking as much as possible without compromising the solution quality. Our evaluation results show that the likelihood that B ird -VNE results in backtracking is small, thus demonstrating its effectiveness in reducing the search space. We analytically and empirically verify that B ird -VNE outperforms existing VNE algorithms with respect to computational efficiency, closeness to optimality, and its ability to avoid potential migrations in mobile wireless networks.

Virtual Network Embedding for telco-grade network protection and service availability

The decoupling of software from hardware by means of virtualization presents us with a unique opportunity to perform on-the-fly network deployment and reconfiguration. Virtual Machines could be instantiated and virtual links can connect these machines to form end-to-end virtualized networks on top of a physical network infrastructure. Virtual Network Embedding (VNE) algorithms could be used to map such virtual network on a physical network infrastructure. However, present VNE algorithms do not consider overall network protection. This is critical for a Telecom operator that needs to realize 99.999% network availability. Moreover, VNE is an NP-hard problem. In this paper, we propose a heuristics VNE aimed at protecting Telecom operator sites. Our objective is to develop advance counter-measures in the form of telco-grade redundancy to avoid large scale network failures such as the one observed during the tsunami in Japan in 2011. In designing our VNE algorithm, we distinguish server nodes from switching nodes as a server function cannot be embedded on a switching node. We also choose not to employ path splitting which is difficult to implement in real network operations. Along with detail modeling of our proposal, we also evaluate our scheme which shows its efficiency in realizing operators' valuable infrastructure protection while maintaining lower resource consumption.

Time Efficient Virtual Network Embedding Algorithm

AbstractThe virtual network embedding problem is an essential problem in network virtualization. Researchers care about efficiency of the virtual network embedding algorithm. This issue has two procedures: node embedding and link embedding. However, previous studies mainly concentrate on the node embedding while neglecting the link embedding, which is the main cause for the bad running time. In this paper, we propose a new algorithm—Deleting-first algorithm, which deletes incapable substrate links for the current virtual request before link mapping. The efficiency of virtual network embedding will be improved. The simulation results show that the average performance of the new algorithm is better at runtime.

A generalized resource allocation framework in support of multi-layer virtual network embedding based on SDN

Network Virtualization (NV) allows multiple heterogeneous architectures to simultaneously coexist in a shared infrastructure. Embedding multiple virtual networks (VNs) in a shared substrate deals with efficient mapping of virtual resources in the physical infrastructure and is referred to as the Virtual Network Embedding problem (VNE-problem). Although there is recently a number of research work in the area of network virtualization based on the Software-Defined Networking (SDN) technology, virtual network embedding in SDN remains challenging from both theoretical and practical points of view.This article focuses on virtual network embedding strategies and related issues for Infrastructure-as-a-Service (IaaS) paradigms under the constraint of fixed virtual node locations. Special considerations are given to the problems related to resource allocation and link sharing of multi-layer virtual networks on top of the physical substrate. Firstly, a heuristic virtual network embedding algorithm is proposed that can improve the mapping acceptance ratio and resource efficiency in the IaaS context. Secondly, REsource reSERvation in generalized Virtual NETworks (ReServNet), a Software-Defined Networking platform designed for embedding multi-level virtual networks in physical infrastructures is developed. By defining new softwarized logical functions, ReServNet allows network administrators to create and manage multiple virtual networks on top of the physical network and allocate bandwidth resources to them accordingly. Moreover, the ReServNet framework allows for designing, prototyping, benchmarking and evaluating the performance of different network embedding algorithms easily in real SDN virtualization environments. Different issues related to virtual network embedding on SDN-based physical substrate are also analyzed and discussed in detail.

Optimization Model and Algorithm for Energy Efficient Virtual Node Embedding

In the existing virtual network embedding algorithms, the minimization of energy consumption for mapping virtual nodes is ignored. By means of the optimization theory and the resource consolidation, we construct an optimization model for energy efficient virtual node embedding. The minimization of energy consumption is solved as the minimal product of energy cost per CPU and allocated CPU from virtual nodes to substrate nodes. Based on the minimal element, an algorithm of energy-efficient virtual network embedding is proposed. Simulation results show the energy gains of the proposed algorithm over the existing heuristic algorithms.

A modified ACO algorithm for virtual network embedding based on graph decomposition

Network virtualization is a promising scheme to solve Internet ossification. A challenging problem in this scheme is virtual network embedding (VNE), which involves efficiently embedding multiple heterogeneous virtual networks into one or more physical networks. The VNE problem is known to be NP-hard and thus requires an approximate algorithm as a solution. This study models the VNE problem based on virtual network topology invariance and analyzes the shortcomings of a general embedding algorithm under different network topologies. A modified ant colony optimization algorithm is proposed based on network topology decomposition. A pre-computation algorithm is first proposed based on ant random walking to accelerate the recognition of the ring characteristics of a network topology. Pre-computation results are used to guide the decomposition of virtual networks and the embedding process of ring structures. The topology of a virtual network is decomposed into a combination of ring structures and tree structures, which have different characteristics. Different embedding algorithms are then designed for these structures. Point-disjoint paths are searched for any two virtual links to ensure the reliability of the network topology in the embedding process. The proposed algorithm shows an enhanced optimization performance, which is better than those of the ViNE-LB and GN-SP algorithms.

An Optimal Virtual Network Mapping Model Based on Dynamic Threshold

To support maximum number of users/applications the concept of virtualization is employed. Network virtualization deals with supporting the concurrent wired/wireless network activities and utilizing the available physical (substrate) network efficiently by implementing an ideal virtual network embedding algorithm. Mapping virtual network requests to substrate network is an important problem and is done to optimize certain characteristic parameters of the network system. Most of the virtual network mapping models consider, mapping of the network requests on a single physical network. This work proposes a model for the virtual network mapping onto multiple substrate networks with the objective to optimize the revenue for the network service providers. In the process, some other parameters such as acceptance ratio of the VN requests etc. also improve. Experimental study reinforces the efficacy of the proposed model.

Survivable virtual optical network embedding with probabilistic network-element failures in elastic optical networks

The elastic optical networks can elastically allocate spectrum tailored for various bandwidth requirements. In addition, different virtual optical networks (VONs) formed by different applications or service providers need to be embedded on the common physical optical network, it brings virtual optical network embedding (VONE) problem. There is no precise standard to measure the survivability of VON from the failure probability view and take minimum VON failure probability as an objective in a VONE problem. In this paper, we investigate a survivable VONE problem from a new perspective. Considering probabilistic physical network-element failures, a novel metric, named virtual optical network failure probability (VON-FP), is introduced to evaluate the survivability of VONs in elastic optical networks. Moreover, a failure-probability-aware virtual optical network embedding (FPA-VONE) algorithm is proposed to deploy VONs on the physical network elements with small failure probability, and finally to decrease the VON-FP and enhance the spectrum utilization effectively.

Virtual network embedding based on real-time topological attributes

As a great challenge of network virtualization, virtual network embedding/mapping is increasingly important. It aims to successfully and efficiently assign the nodes and links of a virtual network (VN) onto a shared substrate network. The problem has been proved to be NP-hard and some heuristic algorithms have been proposed. However, most of the algorithms use only the local information of a node, such as CPU capacity and bandwidth, to determine how to map a VN, without considering the topological attributes which may pose significant impact on the performance of the embedding. In this paper, a new embedding algorithm is proposed based on real-time topological attributes. The concept of betweenness centrality in graph theory is borrowed to sort the nodes of VNs, and the nodes of the substrate network are sorted according to the correlation properties between the former selected and unselected nodes. In this way, node mapping and link mapping can be well coupled. A simulator is built to evaluate the performance of the proposed virtual network embedding (VNE) algorithm. The results show that the new algorithm significantly increases the revenue/cost (R/C) ratio and acceptance ratio as well as reduces the runtime.

Virtual Network Embedding Algorithms Based on Best-Fit Subgraph Detection

One of the main objectives of cloud computing providers is increasing the revenue of their cloud datacenters by accommodating virtual network requests as many as possible. However, arrival and departure of virtual network requests fragment physical network's resources and reduce the possibility of accepting more virtual network requests. To increase the number of virtual network requests accommodated by fragmented physical networks, we propose two virtual network embedding algorithms, which coarsen virtual networks using Heavy Edge Matching (HEM) technique and embed coarsened virtual networks on best-fit sub-substrate networks. The performance of the proposed algorithms are evaluated and compared with existing algorithms using extensive simulations, which show that the proposed algorithms increase the acceptance ratio and the revenue.

Using Heavy Clique Base Coarsening to Enhance Virtual Network Embedding

Network virtualization allows cloud infrastructure providers to accommodate multiple virtual networks on a single physical network. However, mapping multiple virtual network resources to physical network components, called virtual network embedding (VNE), is known to be non-deterministic polynomial-time hard (NP-hard). Effective virtual network embedding increases the revenue by increasing the number of accepted virtual networks. In this paper, we propose virtual network embedding algorithm, which improves virtual network embedding by coarsening virtual networks. Heavy Clique matching technique is used to coarsen virtual networks. Then, the coarsened virtual networks are enhanced by using a refined Kernighan-Lin algorithm. The performance of the proposed algorithm is evaluated and compared with existing algorithms using extensive simulations, which show that the proposed algorithm improves virtual network embedding by increasing the acceptance ratio and the revenue.

Memetic Multi-Objective Particle Swarm Optimization-Based Energy-Aware Virtual Network Embedding

In cloud infrastructure, accommodating multiple virtual networks on a single physical network reduces power consumed by physical resources and minimizes cost of operating cloud data centers. However, mapping multiple virtual network resources to physical network components, called virtual network embedding (VNE), is known to be NP-hard. With considering energy efficiency, the problem becomes more complicated. In this paper, we model energy-aware virtual network embedding, devise metrics for evaluating performance of energy aware virtual network-embedding algorithms, and propose an energy aware virtual network-embedding algorithm based on multi-objective particle swarm optimization augmented with local search to speed up convergence of the proposed algorithm and improve solutions quality. Performance of the proposed algorithm is evaluated and compared with existing algorithms using extensive simulations, which show that the proposed algorithm improves virtual network embedding by increasing revenue and decreasing energy consumption.

Membrane Computing Based Virtual Network Embedding Algorithm with Path Splitting

Network virtualization is recognized as an important enabler technology to diversify the future Internet and the Virtual Network Embedding problem is major challenge to fulfill it. In this paper, we proposed a parallel Virtual Network Embedding algorithm with Path splitting on the basis of membrane Computing (VNEPC). And more importantly, it is one phase embedding algorithm that maps virtual nodes and virtual links in the same phase without decomposing the VNE problem. Extensive simulation results show that our proposed VNEPC algorithm outperforms the existing algorithms in long-term average revenue, acceptance ratio and long-term R/C ratio.

Energy-Aware Virtual Network Embedding

Virtual network embedding, which means mapping virtual networks requested by users to a shared substrate network maintained by an Internet service provider, is a key function that network virtualization needs to provide. Prior work on virtual network embedding has primarily focused on maximizing the revenue of the Internet service provider and did not consider the energy cost in accommodating such requests. As energy cost is more than half of the operating cost of the substrate networks, while trying to accommodate more virtual network requests, minimizing energy cost is critical for infrastructure providers. In this paper, we make the first effort toward energy-aware virtual network embedding. We first propose an energy cost model and formulate the energy-aware virtual network embedding problem as an integer linear programming problem. We then propose two efficient energy-aware virtual network embedding algorithms: a heuristic-based algorithm and a particle-swarm-optimization-technique-based algorithm. We implemented our algorithms in C++ and performed side-by-side comparison with prior algorithms. The simulation results show that our algorithms significantly reduce the energy cost by up to 50% over the existing algorithm for accommodating the same sequence of virtual network requests.

A Novel Virtual Network Embedding Algorithm Based on Improved Artificial Fish-Swarm

A Novel Virtual Network Embedding Algorithm Based on Improved Artificial Fish-Swarm

Topology-aware virtual network embedding based on closeness centrality

Network virtualization aims to provide a way to overcome ossification of the Internet. However, making efficient use of substrate resources requires effective techniques for embedding virtual networks: mapping virtual nodes and virtual edges onto substrate networks. Previous research has presented several heuristic algorithms, which fail to consider that the attributes of the substrate topology and virtual networks affect the embedding process. In this paper, for the first time, we introduce complex network centrality analysis into the virtual network embedding, and propose virtual network embedding algorithms based on closeness centrality. Due to considering of the attributes of nodes and edges in the topology, our studies are more reasonable than existing work. In addition, with the guidance of topology quantitative evaluation, the proposed network embedding approach largely improves the network utilization efficiency and decreases the embedding complexity. We also investigate our algorithms on real network topologies (e.g., AT&T, DFN) and random network topologies. Experimental results demonstrate the usability and capability of the proposed approach.

Virtual Network with Security Guarantee Embedding Algorithms

Network virtualization has been widely concerned as the new technology to remedy the current ossification Internet architecture. Previous virtual network (VN) embedding algorithms focus on optimizing the use of resources with regard to performance with constraints on virtual nodes and links. There are few researches to analyze the security threat to the virtual network. In this paper, we first present two security threats of virtual network and investigate them in depth. Then we propose a novel virtual network with security guarantee that will take the trust value and security protection level as the new security constraints during its embedding. The virtual network with security guarantee embedding algorithm is given at last, and the simulation results show that the algorithm is effective.

ALEVIN - A framework to develop, compare, and analyze virtual network embedding algorithms

Network virtualization is recognized as an enabling technology for the Future Internet. Applying virtualization of network resources leads to the problem of mapping virtual resources to physical resources, known as “Virtual Network Embedding” (VNE). Several algorithms attempting to solve this problem have been discussed in the literature, so far. However, comparison of VNE algorithms is hard, as each algorithm focuses on different criteria. To that end, we introduce a framework to compare different algorithms according to a set of metrics, which allow to evaluate the algorithms and compute their results on a given scenario for arbitrary parameters.