Open Access

ARTICLE

A Cloud-Based Distributed System for Story Visualization Using Stable Diffusion

Chuang-Chieh Lin¹, Yung-Shen Huang², Shih-Yeh Chen^2,*

1 Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, 202301, Taiwan
2 Department of Engineering Science, National Cheng Kung University, Tainan, 701401, Taiwan

* Corresponding Author: Shih-Yeh Chen. Email:

(This article belongs to the Special Issue: Omnipresent AI in the Cloud Era Reshaping Distributed Computation and Adaptive Systems for Modern Applications)

Computers, Materials & Continua 2026, 86(2), 1-19. https://doi.org/10.32604/cmc.2025.072890

Received 05 September 2025; Accepted 11 October 2025; Issue published 09 December 2025

Abstract

With the rapid development of generative artificial intelligence (GenAI), the task of story visualization, which transforms natural language narratives into coherent and consistent image sequences, has attracted growing research attention. However, existing methods still face limitations in balancing multi-frame character consistency and generation efficiency, which restricts their feasibility for large-scale practical applications. To address this issue, this study proposes a modular cloud-based distributed system built on Stable Diffusion. By separating the character generation and story generation processes, and integrating multi-feature control techniques, a caching mechanism, and an asynchronous task queue architecture, the system enhances generation efficiency and scalability. The experimental design includes both automated and human evaluations of character consistency, performance testing, and multi-node simulation. The results show that the proposed system outperforms the baseline model StoryGen in both CLIP-I and human evaluation metrics. In terms of performance, under the experimental environment of this study, dual-node deployment reduces average waiting time by approximately 19%, while the four-node simulation further reduces it by up to 65%. Overall, this study demonstrates the advantages of cloud-distributed GenAI in maintaining character consistency and reducing generation latency, highlighting its potential value in multi-user collaborative story visualization applications.

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Keywords

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