研究目的
To compare two dynamic approaches for solving the routing, modulation, and spectrum allocation problem in elastic optical networks, aiming to minimize utilized spectrum and maximize the number of allocated connection requests.
研究成果
DRSAGA, which uses a genetic algorithm for path selection, provides lower blocking probabilities and more efficient spectrum utilization compared to RMLSRA, especially in networks with shorter links. However, RMLSRA has lower computational time. Future work could explore different genetic algorithm strategies and inclusion of protection mechanisms.
研究不足
The study uses a specific network topology (CORONET) and traffic patterns, which may not generalize to all elastic optical networks. Computational time for DRSAGA is higher, and the algorithms do not consider path protection or spatially-spectrally flexible networking aspects.
1：Experimental Design and Method Selection:
The study compares two algorithms: RMLSRA (routing, modulation level, and spectrum reallocation) based on shortest paths and dynamic reallocation, and DRSAGA (dynamic routing and spectrum allocation genetic algorithm) using a genetic algorithm for path selection. Simulations are conducted to evaluate performance metrics such as blocking probability, spectrum utilization, and computational time.
2：Sample Selection and Data Sources:
The CORONET continental United States network topology with 75 nodes and 99 links is used. Connection requests are generated randomly with Poisson distribution for number of connections, random capacities from [10, 40, 100, 400], and exponential distribution for duration.
3：List of Experimental Equipment and Materials:
No specific physical equipment is mentioned; simulations are implemented in Python software.
4：Experimental Procedures and Operational Workflow:
For each algorithm, simulations are run with different traffic loads and network link lengths (original and scaled-down). Parameters include k=5 shortest paths for RMLSRA, G=5 generations and P=15 population size for DRSAGA, and Q=40 spectrum slots.
5：Data Analysis Methods:
Performance is analyzed based on number of allocated connections, spectrum utilization percentage, blocking probability, and computational time per connection. Results are compared between the two algorithms.
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