Energy Efficient Virtual Network Embedding for Cloud Networks - 2015

PROJECT TITLE:

Energy Efficient Virtual Network Embedding for Cloud Networks - 2015

ABSTRACT:

Network virtualization is widely thought of to be one amongst the main paradigms for the future Internet design because it provides a range of advantages together with scalability, on demand allocation of network resources, and therefore the promise of efficient use of network resources. In this paper, we tend to 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 knowledge centers. We tend to model our approach in an IP 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 value approach (CostVNE) and the energy aware approach (VNE-EA). The CostVNE approach optimizes the employment of accessible bandwidth, whereas the VNE-EA approach minimizes the facility consumption by reducing the amount of activated nodes and links while not taking into account the granular power consumption of the information centers and the 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 information center power profile. We have a tendency to develop a heuristic, real-time energy optimized VNE (REOViNE), with power savings approaching those of the EEVNE model. We tend to conjointly compare the different approaches adopting an energy efficient data center power profile. Furthermore, we tend to study the impact of delay and node location constraints on the energy potency of virtual network embedding. We tend to 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 advantages that VNE offers in optical orthogonal division multiplexing networks.

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