  In this paper, we study problem of efficient service relocation (i.e.,
changing assigned data center for a selected client node) in elastic optical
networks (EONs) in order to increase network performance (measured by the
volume of accepted traffic). To this end, we first propose novel traffic model
for cloud ready transport networks. The model takes into account four flow
types (i.e., city-to-city, city-to-data center, data center-to-data center and
data center-to-data center) while the flow characteristics are based on real
economical and geographical parameters of the cities related to network nodes.
Then, we propose dedicated flow allocation algorithm that can be supported by
the service relocation process. We also introduce 21 different relocation
policies, which use three types of data for decision making - network
topological characteristics, rejection history and traffic prediction.
Eventually, we perform extensive numerical experiments in order to: (i) tune
proposed optimization approaches and (ii) evaluate and compare their efficiency
and select the best one. The results of the investigation prove high efficiency
of the proposed policies. The propoerly designed relocation policy allowed to
allocate up to 3% more traffic (compared to the allocation without that
policy). The results also reveal that the most efficient relocation policy
bases its decisions on two types of data simultaneously - the rejection history
and traffic prediction.
