{'fraction_non_alphanumeric': 0.015181518151815182, 'fraction_numerical': 0.0, 'mean_word_length': 5.890909090909091, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Validation of signal propagation modeling for highly scalable simulations

Efficient information flow in the complex, often microscale simulation systems such as the social, artificial life, or traffic ones poses a significant challenge. It is difficult to implement a highly scalable system due to algorithmic problems, which significantly hamper the efficiency, especially in the case of maintaining a synchronized state in a parallelized, distributed environment. Our previous work presented a desynchronized method of information distribution in a simulation environment, inspired by the propagation of smell, and proved this method to be highly scalable. In this paper, we enhance and validate this method to ensure it does not invalidate the conclusions drawn from the simulation, enabling the development of efficient, scalable simulation systems. The prototype of the method presented here leverages the actor model for parallelization and cluster sharding mechanisms for cluster management, providing a comprehensive solution for large‐scale simulations, following realistic rules known from the nature. In order to validate the method of signal propagation modeling, three simulation models are created and tested. The validation is based on statistical analysis of metrics collected during the simulation execution. Statistical similarity of the results obtained from the distributed and nondistributed executions indicates that the distribution process does not impact the correctness of the simulation.