Network virtualization is widely considered to be one of the main paradigms for the future Internet architecture as it provides a number of advantages including scalability, on demand allocation of network resources, and the promise of efficient use of network resources. In this paper, we propose an energy efficient virtual network embedding (EEVNE) approach for cloud computing networks, where power savings are introduced by consolidating resources in the network and data centers. We model our approach in an IP over WDM network using mixed integer linear programming (MILP). The performance of the EEVNE approach is compared with two approaches from the literature: the bandwidth cost approach (CostVNE) and the energy aware approach (VNE-EA). The CostVNE approach optimizes the use of available bandwidth, while the VNE-EA approach minimizes the power consumption by reducing the number of activated nodes and links without taking into account the granular power consumption of the data centers and the different network devices. The results show that the EEVNE model achieves a maximum power saving of 60% (average 20%) compared to the CostVNE model under an energy inefficient data center power profile. We develop a heuristic, real-time energy optimized VNE (REOViNE), with power savings approaching those of the EEVNE model. We also compare the different approaches adopting an energy efficient data center power profile. Furthermore, we study the impact of delay and node location constraints on the energy efficiency of virtual network embedding. We also show how VNE can impact the design of optimally located data centers for minimal power consumption in cloud networks. Finally, we examine the power savings and spectral efficiency benefits that VNE offers in optical orthogonal division multiplexing networks.Index Terms-Cloud networks, energy efficient networks, IP over WDM networks, MILP, network virtualization, optical OFDM, virtual network embedding.

Abstract-In

Abstract-Environmental sustainability in high capacitynetworks and cloud data centers has become one of the hottest research subjects. In this paper, we investigate the effective use of renewable energy and hence resource allocation in core networks with clouds as a means of reducing the carbon footprint. We develop a Green Virtual Network Embedding (GVNE) framework for minimizing the use of non-renewable energy through intelligent provisioning of bandwidth and cloud data center resources. The problem is modeled as a mixed integer linear program (MILP). The results show that it is better to instantiate virtual machines in cloud data centers that have access to abundant renewable energy even at the expense of traversing several links across the network. The GVNE model reduces the overall CO2 emissions by up to 32% for the network considering solar power availability and data center locations.

A Number of merits could be brought by network function virtualization (NFV) such as scalability, on demand allocation of resources, and the efficient utilization of network resources. In this paper, we introduce a framework for designing an energy efficient architecture for 5G mobile network function virtualization. In the proposed architecture, the main functionalities of the mobile core network which include the packet gateway (P-GW), serving gateway (S-GW), mobility management entity (MME), policy control and charging role function, and the home subscriber server (HSS) functions are virtualized and provisioned on demand. We also virtualize the functions of the base band unit (BBU) of the evolved node B (eNB) and offload them from the mobile radio side. We leverage the capabilities of gigabit passive optical networks (GPON) as the radio access technology to connect the remote radio head (RRH) to new virtualized BBUs. We consider the IP/WDM backbone network and the GPON based access network as the hosts of virtual machines (VMs) where network functions will be implemented. Two cases were investigated; in the first case, we considered virtualization in the IP/WDM network only (since the core network is typically the location that supports virtualization) and in the second case we considered virtualization in both the IP/WDM and GPON access network. Our results indicate that we can achieve energy savings of 22% on average with virtualization in both the IP/WDM network and GPON access network compared to the case where virtualization is only done in the IP/WDM network. INTRODUCTIONThe current mobile system has evolved from circuit-switched based analogue voice network to a formidable system supporting hundreds of thousands of various applications and a very huge number of users. We are just at the dawn of the conversion to ubiquitous high data rate network that connects anything to anything anytime and anywhere. Therefore, the next generation mobile network will not only connect people, but anything that needs the use of its resources. Various devices will join this network such as medical devices, meteorological equipment, traffic and security cameras, household appliances, etc. As a result, the next generation mobile network will affect many spheres of human life and the growth in traffic will continue during the 5G era beyond 2020 [1,2]. Mobile operators and service providers will have to deal with a 1000 fold increase in traffic compared to the levels in 2010 [3] and they have to properly address a number of challenges due to this huge amount of traffic such as bandwidth requirements and power consumption. In order to address the power consumption challenges, in [4] we have proposed an energy efficient virtual network embedding (EEVNE) approach for cloud computing networks. In [5] we have introduced a framework for energy efficient cloud computing over IP/WDM networks. We have examined energy efficient future HDTV in [6] and investigated the role of physical topology optimization on energy efficiency ...

No abstract