Shared Substrate Network Research Articles

Towards learning-based energy-efficient online coordinated virtual network embedding framework

Network virtualization is a highly effective technology for resource sharing within data centers, enabling the coexistence of multiple heterogeneous virtual networks in a shared substrate network, thus achieving resource multiplexing. The efficient embedding of a virtual network onto a substrate network, known as the virtual network embedding (VNE) problem, has been proven to be NP-hard. In response to this challenge, this paper introduces a novel method, named PPO-VNE, which leverages deep reinforcement learning for virtual network embedding. PPO-VNE employs the Proximal Policy Optimization (PPO) algorithm to generate policies and efficiently coordinate node and link mapping. Furthermore, it adopts a hybrid feature extraction approach that combines handcrafted features with features extracted using graph convolutional networks. The proposed reward function takes multiple objectives into account, guiding the learning process. We implemented a prototype of PPO-VNE and conducted experiments based on the simulation environment, in which the substrate network has 100 nodes, with a probability of 0.1 generating edges between any two node, and eventually there will be about 500 physical links. We evaluate the performance of our PPO-VNE approach from the perspective of overall acceptance rate, overall revenue, revenue-to-cost ratio, maximum energy consumption per unit time and revenue-energy consumption coefficient. Comprehensive simulation results in different scenarios show that our PPO-VNE approach achieves the superior performance on most metrics compared with the existing state-of-the-art approaches, where the overall acceptance rate, overall revenue, revenue-energy consumption coefficient are increased by up to 6.4%, 21.3% and 41.4%, respectively, and the maximum energy consumption per unit time are reduced by up to 22.1%.

Energy-Aware Virtual Network Migration for Internet of Things Over Fiber Wireless Broadband Access Network

The virtualized fiber wireless broadband access networks (V-FiWi) paradigm, effectively embedding heterogeneous virtual networks (VNs) originated from the service provider (SP) into shared substrate network (SN) provided by infrastructure provider (InP), plays a tremendous role in meeting the differentiated requirements between wireless frontend subnetwork and fiber backhaul subnetwork to achieve the interoperability of heterogeneous resource allocation. However, most of the existing V-FiWi integration systems mainly focused on the virtual network request (VNR) acceptance ratio, InP revenue, and substrate resource utilization, and they ignored the crucial issue called higher energy consumption cost, which was resulted from the imbalanced consumption of the substrate resource between the arrival and departure of VNR. In this article, we devote to exploring the energy-aware virtual network migration (EA-VNM) problem over the FiWi access technology, aiming to reoptimize the energy consumption while maintaining the high InP revenue and the large substrate resource utilization. In response to this issue, we first represent the service-oriented V-FiWi broadband access network architecture from the perspective of computing, storage, and network resource constraints, in which a migration model consisting of migration node and migration time is explained in detail. Then, we propose an enhanced KM-based energy-aware node migration (EKM-ENM) algorithm to economize on more bandwidth resource. More specially, the EA-VNM technology consists of network topology attributes and global network resources-based node-ranking measurement (NRM) phase, maximum weight matching-based node migration phase, and energy-aware link migration phase via Dijkstra shortest path algorithm. Finally, a rather large number of simulations are analyzed and evaluated numerically. Simulation results suggest that the proposed EKM-ENM algorithm outperforms the traditional embedding algorithms in terms of saving energy cost, decreasing time complexity, and improving VNR acceptance ratio.

Genetic algorithm enabled virtual multicast tree embedding in Software-Defined Networks

The recent network virtualization technology enables the multi-tenancy, where various virtual network requests can share the same physical network by decoupling network services from the underlying hardware architecture. The process of virtual node and link mapping onto a shared Substrate Network (SN) by satisfying the requested network resources (i.e., bandwidth, computing capacity, etc.) is referred to as Virtual Network Embedding (VNE), which is known as an NP-Hard problem. The problem of VNE aims to exhibit one-to-one (unicast) communication. However, the motivation of this research is to explore how to efficiently map virtual networks with one-to-many (multicast) communications, which are in the form of Virtual Multicast Trees (VMTs), onto an SN. This problem differs from the traditional VNE problem and has not been well-studied by the research community. To this end, we propose a novel algorithm, Modified Genetic Algorithm for Virtual Multicast Tree Embedding (MGA-VMTE), to embed VMTs onto a shared SN in this research. The proposed MGA-VMTE algorithm focuses on minimizing the network resource consumption (i.e., bandwidth) under end-to-end delay constraint in the SN while satisfying the computing request of virtual nodes. Our extensive simulations demonstrate that the MGA-VMTE algorithm outperforms the dynamic impact factor and traditional greedy-based virtual multicast tree embedding approaches regarding bandwidth consumption, acceptance ratio, and resource depletion ratio metrics on NSFNET, USNET, Random-60 node, and Random-120 node network topologies.

Repeatable Multi-Dimensional Virtual Network Embedding in Cloud Service Platform

Virtual network embedding (VNE) can effectively deploy virtual networks (VNs) onto shared substrate network (SN) resources. However, with the consistent changing scalability and diversity demands of VNs, traditional VNE methods prove to be a challenging task for current cloud service platforms. Thus, we model a repeatable multi-dimensional virtual network embedding (RMD-VNE) problem for implementing multi-dimensional virtual networks (MD-VNs) that involves real servers, virtual machines, containers, and network simulators. The MD-VN is preprocessed and embedded via a heuristic method denoted as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ReMiDvne</i> . Following its transformation for the containers and simulation networks, the MD-VN topology undergoes a process of coarsening, partitioning, and uncoarsening. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ReMiDvne</i> then applies a topology-aware repeatable embedding solution to complete the embedding stage. Experimental results demonstrate that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ReMiDvne</i> outperforms seven baseline approaches through small-, 1,000- and 10,000-scale VNE simulation experiments. Remarkably, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ReMiDvne</i> improves the average rates of acceptance ratio, revenue, and revenue-cost ratio by up to 40.45, 40.45, and 299.03 percent, respectively, and reduces the average rate of cost by up to 64.16 percent. Furthermore, real-world VNE experiments are conducted based on the OpenStack platform. The results reveal the ability of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ReMiDvne</i> to efficiently reduce communication costs by up to 45.93 and 63.43 percent for download and upload, respectively.

DDS: A Delay-Based Differentiated Service Virtual Network Embedding Algorithm

Network virtualization (NV) is considered a promising technology that may solve the problem of Internet rigidity. The resource competition of multiple virtual networks for shared substrate network resources is a challenging problem in NV called virtual network embedding (VNE). Existing approaches do not consider the differences between multi-tenant requests and adopt a single embedding method, resulting in poor performance. This paper proposes a virtual network embedding algorithm that distinguishes the network types requested by tenants. This method divides virtual network requests into ordinary requests and delay-sensitive requests according to the delay constraints, provides personalized mapping strategies for different networks, and flexibly responds to the resource requirements and quality of service (QoS) requirements of the virtual network. The simulation results show that, compared with other algorithms, the proposed algorithm improves the request acceptance ratio by about 2% to 15% and the substrate network resources are more effectively utilized.

Dynamic Reliability-Aware Virtual Network Embedding for Airborne Tactical Networks

Airborne tactical networks (ATNs) built on network virtualization (NV) can enable efficient information sharing for network-centric warfare by breaking the tight coupling between applications and network infrastructure and thus solving the network ossification problem. With dynamic changes during military missions, the application of virtualization is challenged by the changing demands on network resources when instantiating multiple virtual networks (VNs) on a shared substrate network (SN), known as virtual network embedding (VNE). However, existing dynamic VNE algorithms, mostly designed for wired networks, focus on the dynamic changes of single VN and do not consider the dynamic changes of different VNs. The proper processing of changes of different VNs is beneficial to improve the embedding profits of VNs. On these backgrounds, we investigate the dynamic wireless VNE that processes the dynamic changes of different VNs in the wireless environment of ATNs. A relationship matrix-based dynamic wireless VNE (DWVNE-RM) algorithm is proposed in order to maximize the acceptance ratio of VN requests. The dynamic changes of different VNs are classified into negative changes (requiring resource) and positive changes (releasing resource). Then, the relationship matrix between negative and positive changes is constructed to properly process the resource relationship among different changes in order to improve the acceptance ratio. In addition, the complex interference of ATNs is considered in the mapping or remapping of virtual nodes and links to improve the reliability. Through extensive simulation, DWVNE-RM is compared with multiple existing dynamic algorithms and outperforms over others.

Toward Adaptive Joint Node and Link Mapping Algorithms for Embedding Virtual Networks: A Conciliation Strategy

Network virtualization (NV) has emerged as a momentous facilitator for a notable triumph of future networks by allowing a flexibility, cost-efficiency and on-demand services through the deployment of heterogeneous network service requests on a shared physical infrastructure. The most major challenge of NV is to efficiently and effectively map diversified virtual network requests (VNRs), comprising 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 for simple implementations. Unfortunately, the lack of a coordination between node and link mapping stages might cause low embedding results. In this paper, we present a new approach relied upon Genetic Algorithm (GA), that jointly coordinates virtual node and link mappings where the link mapping is based on three different path searching methods. Moreover, a novel heuristic conciliation mechanism is proposed to deal with a set of possibly infeasible link mappings while exploring embedding solutions within the operations of GA algorithm. Extensive performance results indicate that our proposed GA-based algorithms outperform state-of-the-art virtual mapping algorithms in all evaluation metrics we adopt.

Fault-Tolerant Embedding Algorithm for Node Failure in Airborne Tactical Network Virtualization

Airborne tactical networks (ATNs) are driving the promising development of Internet of Battle things by enabling efficient information sharing, which is impeded by the network ossification problem that is deep-rooted in the tightly coupled network architecture. As a solution, network virtualization (NV) can break the tight coupling between applications and network infrastructure, providing a more flexible and scalable architecture for ATNs. With complex interference and malicious attacks, the application of NV is challenged by network failures when instantiating multiple virtual networks on a shared substrate network, which is known as survivable virtual network embedding (SVNE). However, existing SVNE algorithms, mostly designed for wired networks, are not necessarily optimal for the virtualization of ATNs due to the complex wireless interference. To this end, a fault-tolerant SVNE algorithm, termed SVNE-FT, is proposed to recover virtual networks from single node failure (end or switching node failure) under the wireless interference. To end node failure, SVNE-FT firstly adopts a novel node ranking approach to select reliable substrate nodes for virtual nodes and then remaps the failed virtual nodes, affected by node failure, by releasing part of the substrate paths to improve the resource utilization. In addition, to switching node failure, it adopts the improved pre-configured cycle (p-Cycle) technology to augment the reliable link mapping with differentiated p-Cycles that protect switching node from node failure and reduce the resource consumption of backups. Numerical simulation results reveal that SVNE-FT outperforms typical and latest heuristic SVNE algorithms under the complex interference of ATNs. For instance, average acceptance ratio of virtual networks improves at least 12%.

A Reliable Interference-Aware Mapping Algorithm for Airborne Tactical Network Virtualization

Airborne tactical networks (ATNs) is driving the growing development of network-centric warfare by maintaining coverage and providing reach-back to military units. However, the key function of ATNs is impeded by the network ossification that is deep-rooted in the tightly coupled, vertically integrated architecture of traditional ATNs. Network virtualization (NV) can provide a more flexible and scalable ATN architecture as a solution, breaking the tight coupling between applications and network infrastructure. One important aspect of NV is virtual network embedding (VNE), which instantiates multiple virtual networks on a shared substrate network. However, existing efforts are not necessarily optimal for the virtualization of ATNs due to the absence of QoS-compliant capacity for the complex interference in air-combat field. To tackle this difficulty, a reliable interference-aware VNE algorithm, termed VNE-RIA, is proposed to provide reliable guarantee in the coordinated node and link mapping for various airborne tactical virtual networks (ATVNs). In the node mapping, the VNE-RIA adopts a novel node ranking approach to rank all substrate and virtual nodes, considering the complex interference including link interference, environmental noise and malicious attacks. In the link mapping, an improved anypath link mapping approach, based on the anypath routing scheme, is adopted to improve the reliability and efficiency of mapping virtual links by exploiting the unique features of wireless channels and the influence of different transmission rates. Numerical simulation results reveal that VNE-RIA algorithm outperforms typical and latest heuristic wireless VNE algorithms under the complex electromagnetic interference of ATNs.

On Parallel and Hitless vSDN Reconfiguration

The symbiosis of network virtualization and software-defined networking (SDN) enables an infrastructure provider (InP) to build various virtual software defined networks (vSDNs) over a shared substrate network (SNT). To handle a dynamic network environment, the InP may need to reconfigure the mapping schemes of vSDNs for a variety of reasons. Although previous studies have addressed how to calculate the new virtual network embedding (VNE) schemes for vSDN reconfiguration under different objectives, the transition to migrate vSDNs from their original VNE schemes to new ones is still under-explored. Hence, this article studies how to realize parallel and hitless vSDN reconfiguration, by leveraging the “make-before-break” scenario. We come up with a generic solution to optimize the transition to remap vSDNs to new VNE schemes, such that the remappings can be done in the parallel, hitless and resource-efficient manner, as long as the new VNE schemes are feasible. More specifically, our proposal is the multi-stage parallel vSDN reconfiguration based on maximal connected reconfigurable subgraph (MCRSG). To ensure the efficiency of our proposal, we formulate the optimization for selecting MCRSGs to reconfigure in each stage, and prove the $\mathcal {NP}$ -hardness of the problem. Then, we design an approximation algorithm based on Lagrangian relaxation to solve it time-efficiently. Extensive simulations verify that the proposed algorithm can obtain near-optimal solutions quickly. In addition to the algorithmic study, we also realize our multi-stage parallel vSDN reconfiguration in a practical NVH system, and demonstrate its performance in a real network testbed. Our experimental study identifies in what condition losing of packets during remapping would be inevitable, studies the tradeoff between reconfiguration latency and packet loss rate, and reveal an empirical method to adjust key parameters of our NVH system, for adapting to various network environments.

On Virtual Network Embedding: Paths and Cycles

Network virtualization provides a promising solution to overcome the ossification of current networks, allowing multiple Virtual Network Requests (VNRs) to be embedded on a common infrastructure. The major challenge in network virtualization is the Virtual Network Embedding (VNE) problem, which is to embed VNRs onto a shared substrate network and known to be $\mathcal {NP}$ -hard. The topological heterogeneity of VNRs is one important factor hampering the performance of the VNE. However, in many specialized applications and infrastructures, VNRs are of some common structural features, e.g., paths and cycles. To achieve better outcomes, it is thus critical to design dedicated algorithms for these applications and infrastructures by taking into accounting topological characteristics. Besides, paths and cycles are two of the most fundamental topologies that all network structures consist of. Exploiting the characteristics of path and cycle embeddings is vital to tackle the general VNE problem. In this paper, we investigate the path and cycle embedding problems. For path embedding, we prove its $\mathcal {NP}$ -hardness and inapproximability. Then, by utilizing Multiple Knapsack Problem (MKP) and Multi-Dimensional Knapsack Problem (MDKP), we propose an efficient and effective MKP-MDKP-based algorithm. For cycle embedding, we propose a Weighted Directed Auxiliary Graph (WDAG) to develop a polynomial-time algorithm to determine the least-resource-consuming embedding. Numerical results show our customized algorithms can boost the acceptance ratio and revenue compared to generic embedding algorithms in the literature.

GDM: A General Distributed Method for Cross-Domain Service Function Chain Embedding

Emerging technologies such as network function virtualization (NFV) and software defined networking (SDN) provide a promising way to implement service function chain (SFC), a chain-ordered set of network functions, to support heterogeneous network services through a shared substrate network. A major challenge in this respect is the SFC embedding with respect to constraints of physical resources. Furthermore, for practical purposes, SFC embedding across multiple domains becomes essential. This challenge is referred to as the cross-domain SFC embedding problem, which is intractable due to various reasons, such as the confidentiality of intra-domain information and the domain's local autonomy. In this paper, we propose GDM, a general distributed method for cross-domain SFC embedding. Besides preserving the privacy and autonomy of domains, GDM guarantees fair competition among domains while balancing loads among domains. It first partitions SFC by utilizing an algorithm that can be instantiated to support different embedding goals. Then it allows domains to embed their assigned segments following their policies. Finally, to improve the capability of the whole substrate network to accommodate more SFCs, it implements domain-level load balancing by migrating the deployed VNFs while avoiding excessive influence on the SFC embedding solution. Evaluation results demonstrate that our method performs better in improving acceptance ratio and optimizing domains' embedding goals compared to the existing methods, and it has better scalability.

A Holistic Framework for Virtual Network Migration to Enhance Embedding Ratios in Network Virtualization Environments

Network virtualization is a promising technology for overcoming Internet ossification by enabling multiple Virtual Networks (VNs) to coexist on a shared substrate network. One critical aspect in NV environments is the capability of operators to allocate resources in the substrate network to support VNs in an optimal manner. This is known as Virtual Network Embedding (VNE). In the same context, online VN migration is the process meant to re-allocate components of a VN in real-time and seamlessly to the end-users. Although progress has been made to address VN migration, there has been little investigation on integral migration approaches assessed under different VN environment conditions. The main contribution of this paper is a VN migration framework that addresses the online VN migration problem holistically, namely considering different aspects that affect the efficiency of resource (re)allocations and the VNE acceptance ratios, such as migration policies, trigger conditions, and the CPU capacity requirements for Intermediate Substrate Nodes. An evaluation methodology is developed for analyzing the performance of the proposed framework on substrate infrastructures of different sizes and densities. Extensive software simulations on substrate networks of varying size (50 to 250 nodes) and link density (0.06 to 0.6) discover the migration-oriented parameters that contribute to enhance VNE up to 18.7%. We also compare the framework performance against two state-of-the-art mechanisms that improve online VNE while looking for VNE solutions and observed acceptance ratio enhancements up to 3× higher when using our framework on a physical network with 100 nodes and a density of 0.06.

Cooperative Anomaly Detection With Transfer Learning-Based Hidden Markov Model in Virtualized Network Slicing

Network slicing can partition a shared substrate network into multiple logically isolated virtual networks to support diverse service requirements. However, one anomaly physical node (PN) in substrate networks will cause performance degradation of multiple network slices. To realize the self-organizing management of network slices, a cooperative anomaly detection scheme is designed in this letter through utilizing the transfer learning-based hidden Markov model (TLHMM). The PNs are first classified into four different states. Then, the hidden Markov model (HMM) is used to capture the current states of PNs based on the measurements of virtual nodes (VNs). Finally, according to the learned knowledge of networks and the similarity between PNs, the concept of transfer learning is introduced into HMM to propose a cooperative anomaly detection algorithm. Simulation results demonstrate that the proposed TLHMM-based cooperative anomaly detection algorithm cannot only speed up the learning process, but also achieve an average detection accuracy of more than 90%.

Proactive and Hitless vSDN Reconfiguration to Balance Substrate TCAM Utilization: From Algorithm Design to System Prototype

The combination of network virtualization and software-defined networking enables an infrastructure provider to create software-defined virtual networks (vSDNs) over a shared substrate network (SNT), for supporting new network services more timely and cost-effectively. Meanwhile, as both the services and traffic in the Internet are becoming more and more dynamic, how to properly maintain vSDNs in a dynamic network environment exhibits increasing importance but still has not been fully explored. In this paper, we conduct a study on how to realize proactive and hitless vSDN reconfiguration to balance the utilization of ternary content-addressable memory (TCAM) in a dynamic SNT. Specifically, we consider both algorithm design and system prototyping. From the algorithmic perspective, we try to solve the problems of “what to reconfigure” and “how to reconfigure”. A selection algorithm is designed to proactively choose the virtual switches (vSWs) that should be migrated to other substrate switches for balancing TCAM utilization, i.e., solving what to reconfigure. Then, for the problem of how to reconfigure, i.e., where to re-map the selected vSWs and the virtual links connecting to them, we formulate a mixed integer linear programming model to solve it exactly, and design two heuristics to improve time efficiency. Next, we move to the system part, implement the proposed algorithms in our protocol-oblivious forwarding enabled network virtualization hypervisor system, and conduct experiments to demonstrate proactive and hitless vSDN reconfiguration. The experimental results indicate that our proposal does make vSDN reconfiguration transparent to the vSDNs’ virtual controllers and proactive, and when reconfiguring a vSDN with live traffic, it achieves hitless operations without traffic disruption.

A Self-Adaptive Virtual Network Embedding Algorithm Based on Software-Defined Networks

Network virtualization provides a promising tool to allow multiple virtual networks (VNs) to run on a shared substrate network (SN) simultaneously. VN embedding (VNE) is one of the key technologies of network virtualization. The main goal of VNE is to effectively map VN requests to the SN, which is efficiently utilizes the network resources. The emergence of software defined networks provides a platform for network virtualization to be used and promoted. In a real environment, the resource requirements of tenants are generally different. A single VN mapping algorithm can not effectively handle the multi-demand problem of tenants. We propose a self-adaptive VNE algorithm. VN requests are divided into different types by an adaptive algorithm, we use an integer linear programming formulation to solve VNE problem. This paper considers three different types of VN requests. Type 1 VN requests for high bandwidth requirements, type 2 VN requests for low latency requirements, and type 3 VN requests for high bandwidth requirements and latency requirements. The simulation results show that the virtual network embedding algorithm proposed in this paper can make full use of the SN resources and improve the overall revenue, while effectively dealing with the multi-demand problem of tenants.

Survivable Virtual Network Link Shared Protection Method Based on Maximum Spanning Tree

Network virtualization allows multiple independent and mutual non-interfering virtual networks (VNs) to run simultaneously on a shared substrate network (SN) providing a promising method for overcoming the network ossification. Substrate infrastructure failures occur frequently, most of which are substrate link failures. This has created a research hotspot in the field of survivable VN. In this paper, we add to the research by analyzing the substrate link failures and proposing a survivable VN link shared protection method based on the maximum spanning tree. First, an integer linear programming formulation for the survivable VN link shared protection is established to minimize the backup link bandwidth ratio. Second, an efficient VN mapping algorithm based on optimal matching is designed to make full use of the limited substrate resources. This mapping algorithm that fully considers the topological connections between nodes in the node mapping phase improves the acceptance ratio and the long-term average revenue to cost ratio. Finally, a maximum spanning tree link protection algorithm is proposed, and a reasonable sharing mechanism of backup link resources among different VNs is designed to ensure the VN survivability and reduce the SN resource consumption. The experimental results show that our method not only guarantees the VN survivability but also reduces SN resource consumption.

Energy-Aware Virtual Optical Network Embedding in Sliceable-Transponder-Enabled Elastic Optical Networks

Network virtualization has been widely considered to improve the resource efficiency of network infrastructure by allowing multiple virtual networks to coexist on a shared substrate network. With the exponential growth of Internet traffic, the network energy consumption incurs a considerable increase around the world. In this paper, we consider energy-aware virtual optical network embedding (EA-VONE) issue in flexible-grid elastic optical networks (EONs), while sliceable transponders (TPs) are assumed to be equipped in each node. First, an integer linear programming (ILP) model for the energy-minimized VONE is developed to optimally solve this problem. Due to the non-scalability of the ILP model, we then design two energy-saving policies for data centers (DCs) and TPs in the process of the node mapping and link mapping, respectively. Based on the two policies, two heuristic schemes are also developed: 1) DC-EA scheme, which only considers DC energy-saving in the node mapping procedure and 2) DC&TP-EA scheme, which simultaneously considers the energy-saving for both the DCs in the node mapping and TPs in the link mapping. Moreover, offline and online EA-VONE algorithms are developed. To investigate the benefits of the two energy-saving (i.e., DC-EA and DC&TP-EA) schemes, a benchmark scheme is also realized, which only maintains traffic-balancing (TB) policy without any energy-saving consideration. The simulation results indicate that our proposed DC&TP-EA scheme achieves the maximum power saving efficiency compared with the DC-EA and TB schemes. Also, in the DC-EA and DC&TP-EA schemes, the effect of DC energy saving is very remarkable when the traffic load is smaller. With the increase of traffic load, the DC energy saving may matter less, meanwhile, the TP energy-saving plays a more and more important role. Moreover, both the DC&TP-EA and DC-EA schemes maintain similar blocking performance as that of the TB scheme, which shows the superiority of our proposed schemes.

Node‐Fusion: Topology‐aware virtual network embedding algorithm for repeatable virtual network mapping over substrate nodes

SummaryCloud computing has become a new Internet application model, where network virtualization is recognized as an important technology for allowing multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network (SN). As demands in cloud computing increase, the scale of VN greatly increases as well, and providing an end‐to‐end SN to embed VNs in terms of scale is difficult. To utilize SN resources fully, we devise a topology‐aware Node‐Fusion algorithm, which is different from the traditional virtual network embedding (VNE) algorithms, for repeatable VNE over substrate nodes problem. We rank the resource of nodes through a novel solution by considering the CPU and bandwidth of adjacent link capacity and the number of adjacent links of each node as resources, and rank a node on the basis of resources. Furthermore, we embed several virtual nodes into the same substrate node together in accordance with Node‐Fusion interconnection value during the node mapping process, which can greatly improve the success ratio of the subsequent link mapping phase. Evaluation results confirm that Node‐Fusion outperforms traditional classical heuristics (Link‐opt, Node‐opt, and ORSTA), which are modified to fit into our model, with regard to acceptance ratio, long‐term revenue, long‐term cost, and revenue‐cost ratio.

Topology based reliable virtual network embedding from a QoE perspective

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.