Restoration in optical cloud networks with relocation and services differentiation

Abstract

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Optical cloud networks allow for the integrated management of both optical and IT resources. In this paradigm, cloud services can be provisioned in an anycast fashion; i.e., only the source node asking for a service is specified, while it is up to the cloud control/management system to select the most suitable destination data center (DC) node. During the cloud service provisioning process, resiliency is crucial in order to guarantee continuous network operations also in the presence of failures. On the one hand, a survivability strategy needs to be able to meet the availability requirements of each specific cloud service, while on the other hand it must be efficient in using backup resources. This paper proposes a restoration-based survivability strategy, which combines the benefits of both cloud service relocation and service differentiation concepts. The former is used to enhance the restorability performance (i.e., the percentage of successfully restored cloud services) offered by restoration, while the latter ensures that critical services are given the proper consideration while backup resources are assigned. The paper proposes both an integer linear programming (ILP) formulation, which guarantees optimal results, and a heuristic, which trades the optimality of the solution achieved by the ILP for faster processing times. Simulation results show that the average service availability and restorability performance obtained by both the ILP and the heuristic are very close to that achievable using a protection-based strategy, but with the inherent benefit, in terms of efficient use of resources, offered by a restoration-based approach.Peer ReviewedPostprint (author's final draft