An Overview of Embedding Strategies in Cloud Computing Backbone Networks (original) (raw)
Related papers
A Map of the Clouds: Virtual Network Mapping in Cloud Computing Data Centers
Cloud computing success as a paradigm stems from the concepts its implementation was based on. Dynamic scalability and flexible pay-as-you-go pricing options attract business clients. However, efficient implementation of virtualization is the core that makes all these parts tick. To make that possible, cloud service providers need a thorough virtual network mapping system that allocates computational and network resources in a way that guarantees the quality of service conditions for clients while maximizing providers' revenue and resource utilization. A comprehensive system is introduced to solve virtual network mapping for a set of connection requests sent by cloud clients. Connections are collected in time intervals called windows. Node mapping and link mapping are performed. Different windows size selection schemes are introduced and evaluated. Simulation results show that the Dynamic windows size algorithm achieves cloud service providers objectives in terms of served conne...
Embedding virtual topologies in networked clouds
2011
Embedding virtual topologies in physical network infrastructure has been an area of active research for the future Internet and network testbeds. Virtual network embedding is also useful for linking virtual compute clusters allocated from cloud providers. Using advanced networking technologies to interconnect distributed cloud sites is a promising way to provision on-demand large-scale virtualized networked systems for production and experimental purposes.
A Cluster-Oriented Policy for Virtual Network Embedding in SDN-Enabled Distributed Cloud
International Journal of Computing and Digital Systems, 2022
Resource allocation is a crucial challenge for network virtualization (NV) in a cloud environment. Virtual network embedding (VNE) approaches exemplify NV technologies' critical utility, which must efficiently deal with potential network issues. To promote cloud infrastructure flexibility, software-defined networking (SDN) has been adopted as a network practice to centralize the manageability of the data centre network (DCN) resources. This paper introduces a classification approach that ensures an accurate starting point for solving the VNE problem in a distributed system. The solution implementation is based on measuring the importance of each DCN using the spearman rank correlation coefficient. Afterward, we devise a constructive algorithm that classifies DCNs in clusters from unsupervised data learning. This DCN management allows us to direct the VNE process to a small number of DCNs, which will reduce the dimensionality of the search operation in a distributed environment. Ultimately, we adopt various metaheuristics as a VNE optimizer for the selected DCN. Numerical results verify that the Jenks natural breaks classification outperforms similar methods in terms of resource utilization and acceptance ratio.
Virtual network routing in cloud computing environment
2016 International Conference on Computer Communication and Informatics (ICCCI), 2016
Cloud computing offers on demand services, accessing and availability of resources by means of multiple devices by speedy detecting as required. In cloud computing data centers are consider as a virtual servers and organization or single users pay as the capacity they use (eg:Amazon web services).data centers offers an cloud services by use of virtualization techniques. Compute, network, storage are the principle offering of information facilities.. In networks the data lookup may degrade the network transparency so the importance of the routing is considered as an essential part in the cloud computing since they are based on the on-demand networks. Thus the comprehensive way of different types of routing algorithms in cloud computing environment is surveyed. Here we have compared routing in structured and unstructured overlay network.
An Approach towards Resource Efficient Virtual Network Embedding
2010
Network virtualization is at the heart of efforts to end Internet ossification, and utilize network infrastructure efficiently. The key concept is to share the infrastructure resources among many users at the same time and in such a way to enable them to deploy the required architectures. This leads to virtual networks (VNs), demanding different resources that have to be embedded on the underlying shared infrastructure network. The requirements of a VN can be based on factors such as, the type of traffic it needs to carry. Some portion of the same resources (substrate resources) needs to be assigned to every VN and the substrate resources are also finite. Thus, a mechanism needs to be devised in order to schedule the resources. This embedding process with resource constraints on virtual nodes and links to be applied on the substrate, which also has limited resources, is challenging and corresponds to the category of NP-hard problems. In this paper, we propose an approach to solve this problem by mapping the vertices of the VN as closely as possible in the substrate network and then assigning virtual edges to the shortest paths which satisfy their demands. This could enable the substrate to accommodate more VNs in the same resource database and hence optimize the substrate's bandwidth utilization. To the best of our knowledge closest node mapping proposed in this solution is a novel approach and is evaluated and compared to the existing approach of greedy node mapping in different scenarios. The sensitivity analysis by varying the different parameters and their effect on mapping VNs is also presented.
Virtual Network Embedding: A Survey
IEEE Communications Surveys & Tutorials, 2000
Network virtualization is recognized as an enabling technology for the future Internet. It aims to overcome the resistance of the current Internet to architectural change. Application of this technology relies on algorithms that can instantiate virtualized networks on a substrate infrastructure, optimizing the layout for service-relevant metrics. This class of algorithms is commonly known as "Virtual Network Embedding (VNE)" algorithms. This paper presents a survey of current research in the VNE area. Based upon a novel classification scheme for VNE algorithms a taxonomy of current approaches to the VNE problem is provided and opportunities for further research are discussed.
IEEE Transactions on Cloud Computing, 2016
Cloud computing built on virtualization technologies promises provisioning elastic computing and bandwidth resource services for enterprises that outsource their IT services as virtual networks. To share the cloud resources efficiently among different enterprise IT services, embedding their virtual networks into a distributed cloud that consists of multiple data centers, poses great challenges. Motivated by the fact that most virtual networks operate on long-term basis and have the characteristics of periodic resource demands, in this paper we study the virtual network embedding problem of embedding as many virtual networks as possible to a distributed cloud such that the revenue collected by the cloud service provider is maximized, while the service level agreements (SLAs) between enterprises and the cloud service provider are met. We first propose an efficient embedding algorithm for the problem, by incorporating a novel embedding metric that accurately models the dynamic workloads on both data centers and inter-data center links, provided that the periodic resource demands of each virtual network are given and all virtual networks have identical resource demand periods. We then show how to extend this algorithm for the problem when different virtual networks may have different resource demand periods. Furthermore, we also develop a prediction mechanism to predict the periodic resource demands of each virtual network if its resource demands are not given in advance. We finally evaluate the performance of the proposed algorithms through experimental simulation based on both synthetic and real network topologies. Experimental results demonstrate that the proposed algorithms outperform existing algorithms from 10 to 31 percent in terms of performance improvement.
Joint Policy for Virtual Network Embeddingin Distributed SDN-Enabled Cloud
Virtualization (NV) has been devised as one of the key bases of operativecloud systems. Commonly, Cloud Providers (CPs) seek to design their networkpolicy, especially in a distributed environment. Virtual Network Embedding(VNE) is a functional tool granted by the NV technologies that allow theCPs to manage their physical resources based on the received Virtual Networks(VNs). This paper focuses on the context when a given Virtual NetworkRequest (VNRs) needs to be shared among multiple Data Center Networks(DCNs). The proposed VNE solution executes a two-stage policy where at thefirst stage, the DCNs and VNRs have been managed through a greedy methodto solve the assignment problem. Then, we perform a greedy load-balancingalgorithm to accomplish the VNR mapping stage. The simulation results provedthat the proposed two methods outperformed the compared similar techniques.
ALEVIN - A Framework to Develop, Compare, and Analyze Virtual Network Embedding Algorithms
2011
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.
Virtual network function embedding in real cloud environments
Computer Networks, 2015
Future network architectures will be completely reshaped by the emerging Network Function Virtualization (NFV) paradigm, and telco operators will likely deploy flexible infrastructures based on the cloud, offering programmable connectivity services and computing/storage facilities in the form of Virtual Data Centers (VDCs). This paper introduces and discusses some challenging technical issues associated with this promising approach, with a special focus on the exploitation of industry-relevant cloud platforms, such as OpenStack, and on network-aware optimal placement problem of entire VDCs, taking into account multiple virtual (Virtual Machines-VMs, virtual networks, …) and physical (host capacities, network topology and capacity, …) resources and constraints. The proposed placement, computed for real production OpenStack deployments, not only satisfies the predicted communication for all VDCs deployed atop the same physical data center, but also accounts for the (real) computing overhead due to intense communication load of VMs co-located on the same physical host, such as in the case of Virtual Network Functions (VNF) embedding, typically neglected by similar existing works.