Stochastic planning of dependable virtual infrastructures over optical datacenter networks

This paper focuses on the design of multiple dependable virtual infrastructures (VIs) over converged optical network and IT resources supporting uncertain elastic cloud services. VI dependability is defined as the VI ability to offer resilience in the case of IT resource failures and security guarantees in terms of isolation of VIs that share a common physical infrastructure. The VI planning optimization objective is to minimize the overall energy consumption. To address these issues together with the time variability and uncertainty of elastic cloud services, a novel VI planning scheme based on stochastic linear programming (SLP) is proposed. To cope with the increasing computational complexity inherently imposed in SLP formulations, the sample average approximation technique and Lagrangian relaxation are used to solve the SLP problem in an efficient manner. Our modeling results illustrate interesting trade-offs between the overall energy consumption of the VIs and the dependability impact on the energy consumption and the utilization of the infrastructure resources.