A New Robust Heuristic for Assigning Substrate Network Resources to Virtual Networks

2014 ◽  
Author(s):  
Sarah Kareche ◽  
Sylvain Ductor ◽  
Zahia Guessoum ◽  
Mohamed Mezghiche
Keyword(s):  
Virtual Networks ◽  
Network Resources ◽  
Substrate Network

Assignment of Virtual Networks to Substrate Network for Software Defined Networks

2018 ◽  
Vol 8 (4) ◽  
pp. 29-48
Author(s):  
Ali Akbar Nasiri ◽  
Farnaz Derakhshan
Keyword(s):  
Virtual Network ◽  
Management Service ◽  
Virtual Network Embedding ◽  
Virtual Networks ◽  
Network Embedding ◽  
Network Resources ◽  
Central Controller ◽  
Network Controller ◽  
Physical Resources ◽  
Substrate Network

Assigning multiple virtual network resources to physical network resources, called virtual network embedding (VNE), is known to be non-deterministic polynomial-time hard (NP-hard) problem. Currently software-defined networking (SDN) is gaining popularity in enterprise networks to improve the customizability and flexibility in network management service and reduced operational cost. A central controller in SDNs is an important factor that we need to take care of when we want to assign virtual networks to physical resources. In this work, we address virtual network embedding problems for SDNs. Indeed, our objective is to propose a method to assign virtual networks in the substrate network with minimum physical resources, and also minimizing delays between the virtual network controller and the switches in the virtual network. Our proposed algorithm considers the link and node constraints such as CPU and bandwidth constraints which is necessary to consider when we try to solve virtual network embedding problems.

Cloud-Based Platforms and Infrastructures

2017 ◽  
pp. 47-90
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Virtual Networks ◽  
Network Resources ◽  
Computing Services ◽  
Service Models ◽  
Cloud Computing Services ◽  
Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

scholarly journals A Hybrid Reliable Heuristic Mapping Method Based on Survivable Virtual Networks for Network Virtualization

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Qiang Zhu ◽  
Hui-Qiang Wang ◽  
Guang-Sheng Feng ◽  
Hong-Wu Lv ◽  
Zhen-Dong Wang ◽  
...  
Keyword(s):  
Network Virtualization ◽  
Mapping Method ◽  
Virtual Network ◽  
Virtual Networks ◽  
Ant Colony Optimization Algorithm ◽  
Single Node ◽  
Routing Problem ◽  
Cut Set ◽  
Substrate Network ◽  
Pass Through

The reliable mapping of virtual networks is one of the hot issues in network virtualization researches. Unlike the traditional protection mechanisms based on redundancy and recovery mechanisms, we take the solution of the survivable virtual topology routing problem for reference to ensure that the rest of the mapped virtual networks keeps connected under a single node failure condition in the substrate network, which guarantees the completeness of the virtual network and continuity of services. In order to reduce the cost of the substrate network, a hybrid reliable heuristic mapping method based on survivable virtual networks (Hybrid-RHM-SVN) is proposed. In Hybrid-RHM-SVN, we formulate the reliable mapping problem as an integer linear program. Firstly, we calculate the primary-cut set of the virtual network subgraph where the failed node has been removed. Then, we use the ant colony optimization algorithm to achieve the approximate optimal mapping. The links in primary-cut set should select a substrate path that does not pass through the substrate node corresponding to the virtual node that has been removed first. The simulation results show that the acceptance rate of virtual networks, the average revenue of mapping, and the recovery rate of virtual networks are increased compared with the existing reliable mapping algorithms, respectively.

Cloud-Based Platforms and Infrastructures

2019 ◽  
pp. 84-126
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Virtual Networks ◽  
Network Resources ◽  
Computing Services ◽  
Service Models ◽  
Cloud Computing Services ◽  
Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

Survivable Mapping of Virtual Networks onto a Shared Substrate Network

2013 ◽  
pp. 325-343
Author(s):  
Vishal Anand
Keyword(s):  
Performance Metrics ◽  
Heuristic Algorithms ◽  
Network Virtualization ◽  
Future Internet ◽  
Mixed Integer ◽  
Virtual Networks ◽  
Future Internet Architecture ◽  
Computing Services ◽  
Underlying Network ◽  
Substrate Network

The virtualization of both servers and substrate networks will enable the future Internet architecture to support a variety of Cloud computing services and architectures, and prevent its ossification. Since multiple virtual networks (VN) or virtual infrastructure (VI) and services now share the resources of the same underlying network in a network virtualization environment, it is important that efficient techniques are developed for the mapping of the VNs onto the substrate network. Furthermore, due to the sharing of resources, the survivable design of VNs is also very important, since now even small failures in the substrate network will cause the disruption of a large number of VNs that may be mapped on to the substrate network. In this work, the author studies the problem of survivable virtual network mapping (SVNM) and first formulates the problem using mixed integer linear programming (MILP). The author then devises two kinds of algorithms for solving the SVNM problem efficiently: (1) Lagrangian relaxation-based algorithms including LR-SVNM-M and LR-SVNM-D and (2) Heuristic algorithms including H-SVNM-D and H-SVNM-M. The author then compares the performance of the algorithms with other VI mapping algorithms under various performance metrics using simulation. The simulation results and analysis show that the algorithms can be used to balance the tradeoff between time efficiency and mapping cost.

Constructing Power-Aware Multicast Virtual Networks

2011 ◽  
Vol 308-310 ◽  
pp. 1728-1731
Author(s):  
Ning Qi ◽  
Bin Qiang Wang ◽  
Bo Yuan ◽  
Bo Zhang
Keyword(s):  
Power Consumption ◽  
Greedy Algorithm ◽  
General Public ◽  
Research Community ◽  
Virtual Networks ◽  
Virtual Topology ◽  
Construction Problem ◽  
Construction Algorithm ◽  
Substrate Network

Power consumption of Internet is becoming more and more a sensible problem, which is of interest for both the research community and the general public. In this paper we have formally defined the power-aware multicast VN construction problem and setup an ILP model whose objective is to find a virtual topology on top of substrate network fulfilling all restrictions, while the power consumption of construction is minimized. In order to address the problem efficiently we develop a greedy algorithm: PMVNMH. The efficiency of the power-aware construction algorithm is evaluated by emulation experiment.

scholarly journals Virtual Network Embedding Based on Security Level with VNF Placement

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Dhanu Dwiardhika ◽  
Takuji Tachibana
Keyword(s):  
Network Security ◽  
Virtual Network ◽  
Security Level ◽  
Virtual Network Embedding ◽  
Virtual Networks ◽  
Network Embedding ◽  
Numerical Examples ◽  
Substrate Network ◽  
The Cost

In this paper, in order to embed virtual networks by considering network security, we propose a virtual network embedding based on security level with VNF placement. In this method, virtual networks are embedded in a substrate network by considering security and some security VNFs are placed in order to increase the security level of substrate networks. By using our proposed method, many virtual networks can be embedded by considering security level. As a result, the reward can be increased and the cost of placing VNFs is not increased so much. We evaluate the performance of our proposed method with simulation. The performance of this method is compared with the performance of a method that places VNFs randomly and the performance of a method without placing VNFs. From numerical examples, we investigate the effectiveness of this method. In numerical examples, we show that the proposed method is effective in embedding virtual networks by considering network security.

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