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Exploiting IP‐layer traffic prediction analytics to allocate spectrum resources using swarm intelligence
Author(s) -
Kyriakopoulos Constantine,
Nicopolitidis Petros,
Papadimitriou Georgios,
Varvarigos Emmanouel
Publication year - 2020
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4516
Subject(s) - computer science , particle swarm optimization , computer network , resource allocation , exploit , node (physics) , distributed computing , network topology , algorithm , computer security , structural engineering , engineering
Summary Elastic optical networks emerge as a reliable backbone platform covering the next‐generation connectivity requirements. It consists of advanced enabling components that provide the ability for extensive configuration leading to performance improvement in many areas of interest. Higher layer analytics like data from IP traffic prediction can assist in the process of allocating resources at the optical layer. This way, light connections are established more efficiently while targeting specific performance goals. For that purpose, an algorithm is designed and evaluated that exploits traffic prediction of data transfers between nodes of an optical metro or backbone network. Next, it utilizes adaptive functionality based on particle swarm optimization to find paths with available spectrum resources. These resources can facilitate more efficiently the future traffic demand, since traffic prediction data are considered when finding the related paths. The innovative resource allocation method is evaluated using small and very large real topologies. It scales (in execution time and resource usage) according to node increase, executes in feasible time frames, and reduces transponder utilization resulting to increased energy efficiency.