Improving Cloud-Based IoT Services Through Virtual Network Embedding in Elastic Optical Inter-DC Networks

Abstract

With the boom of Internet of Things (IoT), an increasing amount of data from IoT applications is moved to geo-distributed data centers (DCs) for data analysis. Massive compute-demanding applications call for a more flexible and efficient resource allocation for uncertain and heterogeneous traffic in geo-distributed multi-DC systems. Virtual network embedding, a major part of network virtualization, facilitates to provide different kinds of businesses or services by resource sharing. Moreover, due to their elasticity, elastic optical networks are viewed as a very promising solution to support inter-DC networks. This paper focuses on the effectiveness and spectrum fragmentation problem for virtual optical network embedding in elastic optical inter-DC networks by employing multidimensional resources and a topological attribute. In the node mapping, betweenness of a physical node is considered together with multidimensional resource carrying capacity (MRCC) to identify proper matching. Specifically, to reduce the influence of a spectrum fragment, the available spectrum continuity degree is coupled with the computing capacity of a physical node as the MRCC. In the link mapping, a tightest-matching factor is employed for the selection of paths to accommodate virtual links. Compared with baseline algorithms except for the integer linear programming (ILP) solution, analytical and numerous experiments show that our solution reduces the blocking probability by 30% on average, balances the load by 15% on average and improves spectral efficiency significantly. Moreover, our proposal has a slightly lower spectral efficiency but a better blocking performance and a much better link load balance than that of the ILP formulation.