Green virtualized networks

2013 IEEE International Conference on Communications (ICC), 2013

Network virtualization is a promising technology for the Internet of the Future. An open issue in virtualization is the management of network resources in a way that energy savings are achieved without compromising the Quality of Service (QoS) requirements of the virtual networks. The dynamic allocation and deallocation of virtual networks can lead the state of the substrate to a less than optimum energy consumption. This paper introduces two algorithms for the migration of virtual routers and/or links which aims to allocate resources so that energy consumption is minimized. The efficacy of the migration of virtual routers and/or links and its impact on energy consumption are analyzed based on results derived via simulations.

Procedia Computer Science, 2020

The Information and Communications Technology sector produces approximately 2% of the global carbon footprint every year. Estimations show that by the year 2020, this will grow up to 4% if the communication industry continues on this current path, which will be disastrous for the environment and hence the time for change towards green computing is now. Green networking refers to the processes used to optimize networking functions to make it more energy efficient. Datacenter networking infrastructures rely on power hungry devices to operate. This study will explore some modern enabling technologies such as Software Defined Networking, Edge Computing and Virtualization, and how these distinct concepts can fit together to enable more efficient green network solutions. Simulations carried out in a CloudSim testing environment using an energy cost model measure saving from virtualization and Edge technologies in datacenters.

Computer Networks, 2015

Energy consumption in information and communications technology (ICT) accounts for a large portion of the total energy consumed in industrial countries, which is rapidly increasing. Virtualized network environments (VNEs) have recently emerged as a solution in this technology to address the challenges of future Internet. VNEs also play a fundamental role toward virtualizing data centers. Consequently, it is essential to develop novel techniques for reducing the energy consumption of VNEs. In this paper, we discuss multiple energy-saving solutions that locally optimize the node and link energy consumption of VNEs during the off-peak period by reconfiguring the mapping of already allocated virtual nodes and links. The proposed reconfigurations enable the providers to adjust the level of the reconfiguration and accordingly control possible traffic disruptions. An integer linear program (ILP) is formulated for each solution. Because the defined ILPs are N P-hard, a novel heuristic algorithm is also proposed. The proposed energy-saving methods are evaluated over random VNE scenarios. The results confirm that the solutions save notable amounts of energy in physical nodes and links during the off-peak period.

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 2012

Network Virtualization is acclaimed to be a key component for the Future Internet by enabling the coexistence of heterogeneous (virtual) networks on the same physical infrastructure, providing the dynamic creation and support of different networks with different paradigms and mechanisms in the same physical network. A major challenge in the dynamic provision of virtual networks resides on the efficient embedding of virtual resources into physical ones. Since this problem is known to be N P-hard, previous research focused on designing heuristicbased algorithms; most of them do not consider a simultaneous optimization of the node and the link mapping, leading to non optimal solutions. This paper proposes an integer linear programming formulation to solve the Virtual Network embedding problem, as a simultaneous optimization of virtual nodes and links placement, providing the optimal boundary for each virtual network mapping. A link − node formulation is used and the multi-commodity flow constrain is applied. In addition, a heuristic algorithm for virtual network embedding is also proposed and compared against the optimal formulation. The performance of the Integer Linear Programming formulation and of the heuristic are evaluated by means of simulation. Simulation experiments show significant improvements of the virtual network acceptance ratio, in average additional 10% of the virtual network requests are accepted when using the proposed formulation, which corresponds, in average, to more 7 virtual networks accommodated on the physical network.

Journal of Network and Computer Applications

Network Function Virtualization (NFV) has attracted a lot of attention in the telecommunication field because it allows to virtualize core-business network functions on top of a NFV Infrastructure. Typically, Virtual Network Functions (VNFs) can be represented as chains of Virtual Machines (VMs) or containers that exchange network traffic which are deployed inside datacenters on commodity hardware. In order to achieve cost efficiency, network operators aim at minimizing the power consumption of their NFV infrastructure. This

Network Virtualization is recognized as a key technology for the future internet. Energy-efficiency is one among the most challenges in future networking environments. Network virtualization has caught the attention of the many researchers in recent years. It facilitates the method of making many virtual networks over one physical network. In existing system, if any one of the machine will get broken means that we are able to simply transfer all the information corresponding to that machine to a different machine. Here we tend to concentrated on only data we don't take into account network efficiency, cost and power consumption.to overcome this problem we move to proposed model. During this paper, we tend to propose an energy economical virtual network embedding (EEVNE) approach for cloud computing networks, wherever power savings are introduced by consolidating resources within the network and data centers. We model our approach in an imp over WDM network using mixed integer linear programming (MILP). The performance of the EEVNE approach is compared with 2 approaches from the literature: the bandwidth cost approach (CostVNE) and also the energy aware approach (VNE-EA). The CostVNE approach optimizes the utilization of available bandwidth, whereas the VNE-EA approach minimizes the ability consumption by reducing the amount of activated nodes and links while not taking into consideration the granular power consumption of the information centers and also the completely different network devices. The results show that the EEVNE model achieves a most power saving of 60% (average 20%) compared to the CostVNE model below an energy inefficient data center power profile. we tend to develop a heuristic, real-time energy optimized VNE (REOViNE), with power savings approaching those of the EEVNE model. we tend to additionally compare the various approaches adopting an energy efficient data center power profile.

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011, 2011

Network virtualization is a promising technique for building the Internet of the future since it enables the low cost introduction of new features into network elements. An open issue in virtualization is how to search for an efficient mapping of virtual network elements onto those of the existing physical network, also called the substrate network. Mapping is an NP-hard problem and existing solutions ignore various real network characteristics in order to solve problem in a reasonable time frame. This paper introduces two new algorithms for the solution of the mapping problem, both based on 0-1 integer programming, for the solution of the mapping problem which consider a whole new set of network parameters not taken into account by previous proposals. Simulation experiments confirm the efficiency of the proposed algorithms.

IEEE/ACM Transactions on Networking, 2019

Network virtualization is an inherent component of future internet architectures. Network resources are virtualized from the underlying substrate and elastically provisioned and offered to customers on-demand. Optimal allocation of network resources in terms of utilization, quality of service, and energy consumption has been a challenge. Existing solutions consider congestion control in a single-objective virtual network embedding (VNE) problem. This paper defines a multiple-objective VNE problem called the congestion-aware, energy-aware VNE (CEVNE). The aim is to seek a solution that saves cost, saves energy and avoids network congestion simultaneously. CEVNE's modelling techniques and solution approaches apply both the weighting method and the constraint method to search for paretooptimal solutions that produce the best compromised solutions for all three objectives. Solving VNE problem is, however, NP-hard. A heuristic solution is proposed involving a two-stage coordinated CEVNE. The node-mapping algorithm searches for the suboptimal solutions for three objectives. The link mapping process is an SDN-based heuristic algorithm that deploys a path service and a resource monitoring application on an SDN controller. The solution is realized using SDN, Segment Routing, and open network operating system platform (ONOS) technologies. The energy minimization is implemented with a registry that keeps track of active nodes and sets inactive nodes to sleep mode. The evaluation results showed that the multiple-objective CEVNE approach is feasible and achieves its goals of optimizing the resource allocation, improving the runtime, saving the energy consumption and controlling the network congestion.

International Journal of Network Management, 2013

Data centers play a crucial role in the delivery of cloud services by enabling on-demand access to the shared resources such as software, platform and infrastructure. Virtual machine (VM) allocation is one of the challenging tasks in data center management since user requirements, typically expressed as service-level agreements, have to be met with the minimum operational expenditure. Despite their huge processing and storage facilities, data centers are among the major contributors to greenhouse gas emissions of IT services. In this paper, we propose a holistic approach for a large-scale cloud system where the cloud services are provisioned by several data centers interconnected over the backbone network. Leveraging the possibility to virtualize the backbone topology in order to bypass IP routers, which are major power consumers in the core network, we propose a mixed integer linear programming (MILP) formulation for VM placement that aims at minimizing both power consumption at the virtualized backbone network and resource usage inside data centers. Since the general holistic MILP formulation requires heavy and long-running computations, we partition the problem into two sub-problems, namely, intra and inter-data center VM placement. In addition, for the inter-data center VM placement, we also propose a heuristic to solve the virtualized backbone topology reconfiguration computation in reasonable time. We thoroughly assessed the performance of our proposed solution, comparing it with another notable MILP proposal in the literature; collected experimental results show the benefit of the proposed management scheme in terms of power consumption, resource utilization and fairness for medium size data centers.

2019

Network virtualization is an inherent component of future internets. Network resources are virtualized and provisioned to users on demand. The virtual network embedding entails two processes: node mapping and link mapping. However, efficient and practical solutions to the link mapping problem in software-defined networks (SDN) and data centers are still lacking. This paper proposes a solution to the link mapping process that can dynamically interact with the routing protocols of the substrate network to allocate virtual link requests to the underlying substrate links and satisfies optimizing cost, minimizing energy consumption, and avoiding congestion (CEVNE LiM) concurrently. CEVNE LiM is realized as a composite application on top of the SDN controller running the Segment Routing (SR) application. The performance of the CEVNE LiM algorithm is compared with the k-shortest path (link mapping) algorithm and shows its superior performance in terms of the overall runtime, the average path length, the average node stress, the average link stress and the overall energy consumption.