Multi-objective Optimization for Resource Allocation in Elastic Optical Networks: Integrating Spectrum and Power Assignment

Abstract

Abstract The increasing demand for bandwidth in modern communication networks has highlighted the need for efficient and dynamic resource allocation. Elastic Optical Networks address this challenge by enabling flexible spectrum and power assignment. This paper proposes an advanced resource allocation technique based on multi-objective optimization (MOO) to jointly optimize spectrum and power, mitigating nonlinear impairments and enhancing network performance. When a connection request arrives at the Call Admission Control, all possible frequency slot demands are generated by combining the requested bit rate with the available modulation formats. The Min Slot Continuity Capacity Loss (MSCL) heuristic selects routes and slot sets to minimize allocation capacity loss for each modulation level. From this process, a matrix of frequency slot combinations is built and subsequently explored by the MOO framework. The proposed method integrates the MSCL heuristic with power assignment to reduce spectrum fragmentation and select optimal power levels, thereby improving the optical signal-to-noise ratio. By jointly considering spectrum positioning, channel powers, amplified spontaneous emission noise, and nonlinear effects, the approach achieves significant performance gains. Simulation results demonstrate that the proposed method outperforms the Power and MSCL (P-MSCL) algorithm, achieving an approximately 11% reduction in blocking probability under a 180 Erlang load in the NSFNET topology with identical parameters.