Optical clouds are the combination of optical transport networks and cloud computing,
which allows the integrated management of both infrastructures in one controller element.
In this paradigm, cloud services can be provisioned in an anycast fashion, i.e., only the
source node asking for a service and the amount of IT resources are specified, while it
is up to the cloud control/management system to select the most suitable destination
datacenter (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
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. Service relocation (i.e., the ability to live re-allocate one provisioned service to
another DC) is one of the new features that can be used in this new paradigm, but needs
to be applied carefully given its associated overhead may overload the network and DCs.
Current works in the literature consider a single service model that lack representation of
the heterogeneity expected for cloud services. In this context, some disrupted connection
properties can be considered to improve the network survivability during the restoration
process, e.g., priorities and service remaining holding time. This thesis 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. An ILP and a heuristic are presented in order to
solve the proposed survivability strategy. The proposed strategies are evaluated considering
a variety of different simulation scenarios. Results show that performance achieved
by the proposed ILP and heuristic are close to the ones achieved when using protection
strategies, but with the inherent benefits in terms of efficient use of resources offered by
restoration-based approaches.
|
