Restoration in Optical Cloud Networks With Relocation and Services Differentiation

Abstract

Abstract-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 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 the one achievable using a protection-based strategy, but with the inherent benefit, in terms of efficient use of resources, offered by a restoration-based approach.

Restoration Based on Bandwidth Degradation and Service Restoration Delay for Optical Cloud Networks

“…Aiming to minimize both the number of cloud services not restored and the amount of resources used for restoration, a restored cloud service is provisioned using only half of the wavelength capacity. The restoration strategy proposed by the authors in [2] combines the benefits of both cloud service relocation and service differentiation concepts aiming to enhance service restorability making sure that different services receives appropriated priorities.…”

“…Protection strategies are based on the allocation of redundant optical resources, to be used only in the occurrence of a failure. As a result, these strategies guarantee 100% recovery but have an inherent cost in terms of resource efficiency (i.e., protection resources are most of the time unused) [2]. In order to reduce such cost, operators may use strategies based on the restoration concept.…”

“…After the occurrence of a failure, the affected lightpaths are re-routed (based only on the available optical resources) in order to restore as many cloud services as possible. As a result restoration strategies are more resource efficient, but cannot guarantee 100% recovery [2].…”

A survey on network resiliency methodologies against weather-based disruptions

“…The disaster recovery mechanism selection focuses on disaster detection mechanisms (e.g., periodical probing of DC sites, or using alarms), VM recovery mechanisms (e.g., using VM snapshots), and network reconfiguration mechanisms (typically relying on anycast) [37]. A cloud resiliency approach that utilizes service relocation and service differentiation for restoration of cloud services after a single-link failure was proposed in [38]. The paper leverages on the anycast nature of cloud services to improve service restorability by relocation to a datacentre with enough available IT (storage and processing) resources when the shortage of network resources prohibits restoration to the DC used by the failed working path.…”

Optimizing Resource Allocation in Hierarchically Distributed Data Centers

“…Traditionally, the approaches proposed in the literature focus solely on a single layer of the architecture as in [da Silva et al 2016], [Mei et al 2017], [Upadhyaya and Ahuja 2017], ignoring the proliferation of DCs in the various layers of the network . They also overlook the DCs capacity to support a large amount of applications with different performance requirements.…”