DICONET project is targeting a novel approach to optical networking providing a disruptive solution for the development of the core network of the future. It is the vision and goal for DICONET to provide ultra high speed end-to-end connectivity with quality of service and high reliability through the use of optimised protocols and routing algorithms that will complement a flexible control and management plane offering flexibility for the future network infrastructure. DICONET investigates, designs, implements and tests new routing and wavelength assignment algorithms considering as constraints physical impairments that arise in transparent core networks. These algorithms will be incorporated into a novel dynamic network planning tool that would consider dynamic traffic characteristics, varying physical impairment and component characteristics and a reconfigurable optical layer. The use of this novel planning tool in conjunction with proper extensions to the control plane of core optical networks that will be designed, implemented and tested by our consortium will make possible to realize the vision of transparency, while offering efficient resource utilization and strict quality of service guarantees based on certain service level agreements. The combinations of the tools, algorithms and protocols that will developed by the uniquely qualified DICONET consortium together with new technologies and architectures that will be considered as enablers for the network of the future will assist in overcoming the expected long term limitations of current core network capabilities. The DICONET scope and objectives, address dynamic cross-layer network planning and optimization while considering the development of a future transport network infrastructure which ensures fail-safe network configuration and operation. Our approach will greatly contribute as a basic element in achieving resilience and transparency of the Future Internet"
The laboratory is active in developing new multi-objective optimization algorithms for solving the impaiment aware RWA problem using either metahuristics or converting the problem to a single objective optimization problem.