Multi-domain grooming algorithm based on hierarchical integrated multi-granularity auxiliary graph in optical mesh networks

Authors:
Jingjing Wu;Lei Guo;Weigang Hou
Affiliations:
College of Information Science and Engineering, Northeastern University, Shenyang, China 110819;College of Information Science and Engineering, Northeastern University, Shenyang, China 110819;College of Information Science and Engineering, Northeastern University, Shenyang, China 110819
Venue:
Photonic Network Communications
Year:
2012

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Abstract

With the size of traffic demands ranges from sub-wavelength-level to wavelength-level, traffic demands need to be aggregated and carried over the network in a cost-effective manner to make sure that the resources are utilized effectively. Therefore, the technique called multi-granularity grooming is proposed to save the cost by reducing the number of switching ports in optical cross-connects. However, the existing multi-granularity grooming algorithms are mostly limited in single-domain optical networks. Since the current optical backbone keeps enlarging and is actually divided to multiple independent domains for achieving the scalability and the confidentiality, it is necessary to study the multi-granularity grooming in multi-domain optical networks. In this paper, we propose a new heuristic algorithm called hierarchical multi-domain multi-granularity grooming (HMMG) based on hierarchical integrated multi-granularity auxiliary graph (H-IMAG) to reduce the total number of optical switching ports. The H-IMAG is composed of the inter-domain virtual topology graph (VTG) and the intra-domain integrated layered auxiliary graph (ILAG), where VTG includes a wavelength virtual topology graph (WVTG) and a waveband virtual topology graph (BVTG), and ILAG includes a wavelength layered auxiliary graph (WLAG) and a waveBand layered auxiliary graph (BLAG). Then, we can groom the sub-wavelength-level demands into lightpaths based on WVTG and WLAG and groom the wavelength-level demands into high-capacity wavebands based on BVTG and BLAG. Simulation results show that performances of H-IMAG can be significantly improved compared with previous algorithm.