Virtual network mapping with traffic matrices

RETRACTED: A Global Optimal Mapping Method of Network based on Discrete Optimization Firefly Algorithm

In the paradigm of cloud computing, multiple users can share the cloud infrastructure resources. The application or service requests from a user can be abstracted as a virtual network (VN) request and submitted to the cloud-based data centers. How to map a virtual network onto the cloud infrastructure network is a challenging issue in cloud resource provisioning. Current researches about virtual network mapping problem mainly focus on resource efficiency, which can be classified into resource efficient VN mapping or cost efficient VN mapping. However, the amount of power or energy consumed by data centers takes a large part of all of the power consumption. This may not only leads to a higher expenditure on the operation of data centers but also contribute to carbon emissions and the greenhouse effect. In this work we study the problem of power efficient virtual network mapping and propose a framework and algorithm for solving this problem. The simulation results show that our approach performs well.

A dynamic and resource sharing virtual network mapping algorithm

Network softwarization technologies, such as software defined networking (SDN), network virtualization (NV), and network function virtualization (NFV), emerge and have been greatly promoted by their supporters. This softwarization scheme contributes to isolating network control from data panel, and allocating virtualized physical network resources flexibly. However, physical switches and links, supporting the softwarization scheme, may be attacked by malicious attackers. Even if these switches and links are softwarized and virtualized successfully, the problem of mapping various virtual network requests, known as virtual network embedding, is difficult to solve directly. Each customized VN request must be allocated and implemented in the appropriate manner. To deal with these issues, we research the virtual network mapping for secure SDN-enabled networks. Firstly, a hierarchical virtualization architecture for SDN- enabled networks is presented. Then, the security model for different malicious attacks is presented. Thirdly, we propose the novel and secure virtual network mapping framework, labeled as \textit{NoViSec}, for supporting SDN-enabled networks. Preliminary experiment results are plotted and discussed so as to validate the effectiveness of our secure \textit{NoViSec} framework.

VHub: Single-stage virtual network mapping through hub location

How to efficiently map the nodes and links in a given virtual network (VN) to those in the substrate network (SN) so that the residual substrate network (RSN) can host as many VN requests as possible is a major challenge in virtual network embedding. Most research has developed heuristic algorithms with interactive or two-stage methods. These methods, however, could cause the RSN fragmented into several disconnected components that are insufficient to host a large number of given VN requests. Without loss of generality, we assume that SNs, as the Internet, are small world and scale free, meaning that the average number of hops between any two nodes is a small constant and that most nodes have small degrees while only a small number of nodes have large degrees. Taking advantage of these two properties, we devise in this paper a new twostage VN embedding approach to improve the connectivity of the residual substrate network so that it has the capacity to host more VN requests. Our algorithm uses a greedy strategy that maps neighboring VN nodes to substrate nodes whose distances are bounded by a small constant. We also map the edge nodes of given VN, i.e., nodes with small degrees, to nodes with large degrees in the SN. We then map the links by solving shortest path problems. Our experimental evaluations show that our algorithms offer better mappings and results in significantly fewer rejections for VN requests.

The cloud offers more services across multiple infrastructures and rapidly growing areas of development in medical care. In the cloud, Network virtualization allows multiple isolated virtual networks (VNs) for flexible sharing of network resources. The virtual network mapping in Network virtualization provides the dynamic virtual node and link resources to satisfy the user needs. The major challenges of cloud computing are optimally and resourcefully responds to each user service requests with minimum time. To address these problems in distributed and hybrid cloud environments, Multicriteria Dragonfly based Graph Theory Resource Optimized Virtual Network Mapping (MD-GTROVNM) technique is introduced. The main objective of the MD-GTROVNM technique is to improve the efficiency of virtual network request mapping with less resource utilization. In the MD-GTROVNM technique, Multicriteria Dragonfly based Graph Theory performs both virtual node mapping and link mapping with reasonable resource utilization such as CPU, memory, and bandwidth. In node mapping, the Multicriteria Dragonfly optimization technique is applied to find the optimal physical node among the population that satisfies the resource constraints. The proposed Multicriteria Dragonfly optimization algorithm achieved a more optimal solution for virtual network mapping. The experimental scenario is carried out with various parameters such as mapping efficiency, computation time, Request acceptance ratio and memory consumption with a number of VN requests. The observed results confirm that the MD-GTROVNM technique effectively increases the mapping efficiency, Request acceptance ratio and minimizes the computation time as well as memory consumption when compared to the existing techniques.

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.

A major challenge in virtual network embedding is to find an efficient mapping of each virtual network (VN) to the nodes and links in the substrate network (SN) so that the residual SN can host as many VN requests as possible. This network optimization problem has been shown to be NP hard. In this paper we propose a “border matching” mechanism in VN embedding, which is shown to outperform a number of existing VN embedding algorithms. In particular, we devise an iterative algorithm called “VNE-B”. Typical VN embedding algorithms may cause fragmentations of the substrate network, i.e. the substrate resources are fragmented into small isolated pieces, making it unable to meet larger future VN requests. VNE-B starts the mapping from the “border” nodes of both VNs and the SN for reducing fragmentation of SN resources. Our experimental evaluations show that VN embedding algorithms with VNE-B result in more efficient mappings and thus fewer rejections for VN requests. We also visualize the residual SN to demonstrate the effectiveness of VNE-B.

A cloud computing paradigm enables users to access services, applications, and infrastructure resources by using thin clients anywhere and at any time. In this paradigm, multiple users can share cloud infrastructure resources. The application or service requests from a user can be abstracted as a virtual network (VN) request and can be submitted to the cloud-based data centers. How to map a VN onto the cloud infrastructure network is a challenging issue in cloud resource provisioning. Thus, efficient mapping techniques that intelligently use the resources of cloud infrastructure are important and necessary. Current research on VN mapping and design focuses on resource-efficient VN mapping or cost-efficient VN mapping. However, there is another important issue in cloud-based data centers that we must pay attention to, i.e., the amount of power or energy that is consumed by a data center. The power consumption in data centers can be a significant percentage of the total power consumption, and it not only leads to a higher data center operating cost but also contributes to carbon emissions and the greenhouse effect. In this paper, we propose a power-efficient resource provisioning technique in cloud-based data centers while complying with service level agreements. We first model a power-efficient VN provisioning problem as a mathematical optimization problem, with the objective of minimizing the power consumption by employing mixed-integer programming. We then propose a heuristic algorithm to efficiently solve this model since this optimization problem is NP-hard. We validate and evaluate our framework and algorithm by conducting extensive simulations on different cloud infrastructure networks under various scenarios. The simulation results show that our approach performs well.

The network architecture of the current Internet cannot accommodate the deployment of novel network-layer protocols. To address this fundamental problem, network virtualization has been proposed, where a single physical infrastructure is shared among different virtual network slices. A key operational problem in network virtualization is the need to allocate physical node and link resources to virtual network requests. While several different virtual network mapping algorithms have been proposed in literature, it is difficult to compare their performance due to differences in the evaluation methods used. In this paper, we proposed VNMBench, a virtual network mapping benchmark that provides a set of standardized inputs and evaluation metrics. Using this benchmark, different algorithms can be evaluated and compared objectively. We present such an evaluation using three existing virtual network mapping algorithms. We compare the evaluation results of our synthetic benchmark with those of actual Emulab requests to show that VNMBench is sufficiently realistic. We believe this work provides an important foundation to quantitatively evaluating the performance of a critical component in the operation of virtual networks.

As the most promising solution to sustain network capacity scaling beyond the fundamental nonlinear Shannon limits of standard single-mode fibers, space division multiplexing (SDM) has attracted enormous attention. To utilize the dimension of “space”, including mode-division multiplexing (MDM) using multi-mode (few-mode) fibers and core multiplexing using multi-core fibers, SDM can substantially increase the spectral bandwidth of a fiber-optic communication channel. In SDM optical networks, virtual network mapping becomes very complex, because the resource dimension has increased, meanwhile redundant resources and multi-dimensional resource fragments are more difficult to deal with, which will increase the blocking probability and decrease the utilization of spectrum resources. On the other hand, many connection requests with high quality of service (QoS) need physical network to provide high survivability for network resources to resist virtual link or virtual node failure. It determines the physical paths and the appropriate resources that are used to support a virtual network with predefined characteristics. A novel algorithm for the problem of shared backup path protected routing, spectrum and mode allocation (SBPP-RSMA) under dynamic traffic conditions is proposed, so as to protect virtual network and enhance the network resource utilization with lower blocking effectively and increase share ratio of spectrum resources. Finally, performance of our novel algorithm in terms of blocking probability and spectrum utilization is discussed with some simulation results.

Network slicing, a key technology for 6G communications, allows diverse services to coexist on a shared physical infrastructure by allocating different resources to virtual networks (VNs, or equivalently, “network slices”) mapped over the shared infrastructure. However, it presents challenges in terms of failure survivability, as the failure of one physical element can lead to the failure of multiple VNs mapped to it, making survivability of ultra-reliable services against multiple failures a crucial research topic. In this study, we investigate the Survivable Virtual Network Mapping (SVNM) problem, focusing on double-link failures. SVNM against double-link failures can be guaranteed by enforcing appropriate SVNM constraints (e.g., any double-link failure cannot disconnect any virtual node from other virtual nodes in the same VN), but this approach requires excessive redundant capacity deployment. To address this issue, we propose a novel technique called SVNM with Inter-VN Capacity Sharing (SINC), which allows capacity sharing across different VNs to improve survivability against double-link failures with efficient spare capacity utilization. Since SINC may fail to reconnect some VNs due to insufficient spare capacity, we propose combining it with a spare slice (a VN fully dedicated to enhancing survivability) to create an advanced version, SINC+, which improves survivability by reconnecting VNs with additional spare capacity. We then formulate both SINC and SINC+ through Integer Linear Programming (ILP) models, which can provide optimal solutions. Moreover, to address the computational limitations of the ILP formulation, we developed scalable heuristic algorithms applicable to both SINC and SINC+ with a small optimality gap. Our numerical results show that VN availability using SINC improves by up to 9.48% over SVNM, with the same total link resource consumption (TLRC). Furthermore, SINC+ ensures VN survivability against all potential double-link failures, and the additional TLRC can be reduced to less than 1% in presence of a high number of VNs or large nodal connectivity, underscoring the sustainability of our proposed solutions.

Network virtualization is becoming one of the most promising ways to solve resource solidification problem of fiber-wireless access networks. To fully utilize substrate resources, a virtual resource embedding method including three sub-mechanisms is presented in this paper. The first one is the priority-based virtual network request (VNR) selecting mechanism, which sorts VNRs and preferentially selects higher priority VNRs for embedding. Then a dynamic embedding mechanism based on load balancing is presented to increase the acceptance rate of VNRs. Second, when embedding is saturated, an embedding update mechanism is proposed to deal with the arrival of new VNRs. It promotes the acceptance rate of high-priority VNRs and the revenue of the infrastructure provider (InP). Finally, a backup resource sharing mechanism is designed to improve reliability, which enables backup resources to be shared and responds to the failures with minimal resources. The simulation results show that the proposed embedding method can balance the resource consumption better than the Greedy Node Embedding and Shortest-path Link Embedding Algorithm, as well as the Greedy Node Embedding and Maximum Residual Bandwidth Link Embedding Algorithm. Besides, by applying our proposed algorithm, higher VNR acceptance rate, InP revenue, and resource utilization are achieved.

In the software defined optical network (SDON) for virtual network services, there still exists unbalanced traffic load distribution in SDON. The traditional load balance mapping method exists in the problem of heavy load of key nodes in optical network and low request acceptance rate of virtual network. In this paper, a virtual mapping method of optical network based on topology awareness is proposed. When the controller of optical network is defined by software, the topology information of nodes and links in the whole network is acquired, and the relative balance weight of each node and link is calculated by combining the connectivity factor. When the virtual network service arrives, the optical network is based on the bandwidth of virtual network service the method of node mapping and link mapping is needed to improve the success rate and balance of virtual network mapping, and avoid the local overload of optical network resources.