Efficient Embedding of Virtual Networks to Distributed Clouds Via Exploring Periodic Resource Demands

Abstract

Cloud computing built on virtualization technologies promises provisioning elastic computing and bandwidth resource services for enterprises that outsource their IT services as virtual networks. To share the cloud resources efficiently among different enterprise IT services, embedding their virtual networks into a distributed cloud that consists of multiple data centers, poses great challenges. Motivated by the fact that most virtual networks operate on long-term basis and have the characteristics of periodic resource demands, in this paper we study the virtual network embedding problem of embedding as many virtual networks as possible to a distributed cloud such that the revenue collected by the cloud service provider is maximized, while the Service Level Agreements (SLAs) between enterprises and the cloud service provider are met. We first propose an efficient embedding algorithm for the problem, by incorporating a novel embedding metric that accurately models the dynamic workloads on both data centers and inter-data center links, provided that the periodic resource demands of each virtual network are given and all virtual networks have identical resource demand periods. We then show how to extend this algorithm for the problem when different virtual networks may have different resource demand periods. Furthermore, we also develop a prediction mechanism to predict the periodic resource demands of each virtual network if its resource demands are not given in advance. We finally evaluate the performance of the proposed algorithms through experimental simulation based on both synthetic and real network topologies. Experimental results demonstrate that the proposed algorithms outperform existing algorithms from 10 % to 31 % in terms of performance improvement. Show more