Energy Optimized Virtual Network Embedding With Location Constraint in the Enterprise Network

To satisfy enterprise demands of analyzing and dealing with the large scale of data with lower costs, an effective method is to integrate the servers and computers and use virtualization technology to construct an enterprise network. Prior studies on network virtualization have mainly been executed in the cloud; however, these studies may not be appropriate for enterprise networks for two reasons: i) the goal of most of them is to generate more revenues for cloud providers, but focus less on saving costs; ii) the physical machines are relatively concentrated in the cloud platform but dispersed over different geographic locations in enterprise networks. In this paper, we solve the problem of energy-optimized virtual network embedding with location constraints (EO-VNE). First, the node and link capabilities in enterprise networks are defined in the form of complex number theory, unifying computers and virtual requests. Second, the normalized method of computing and storage capabilities are proposed to identify the node capability. Third, an energy model of the enterprise network is built, and using this model, EO-VNE is shown to be NP-complete. Finally, an energy-optimized virtual network embedding with a location constraint algorithm (EOLC) is proposed to minimize the energy consumption under the constraint of node position. The experiments show that EOLC consumes less energy compared with the algorithm of energy-aware virtual network embedding with dynamic demands (EAD). It also has better performance than the location constraint algorithm based on bisection (GLC).