Research on Optimization of Efficient Animation Video Production Process Driven by Cloud Computing

DOI

10.2991/978-94-6239-737-8_72How to use a DOI?

Keywords

Cloud Computing; Animation Video; Efficient Production; Distributed Rendering; Real-time Collaboration; Process Optimization

Abstract

To address scattered computing power, repeated asset transfer, low material reuse and weak collaboration in traditional animation production, this paper proposes a cloud computing-driven optimization scheme. The research boundary is clarified as the workflow from asset import, online editing, task decomposition and distributed rendering to collaborative review and final output. A six-layer architecture separates user interaction, gateway access, business services, middleware support, elastic computing and external integration. A priority-aware distributed rendering scheduling policy is further formulated by considering frame complexity, deadline urgency, resource load, task dependency and material locality. The system integrates Spring Boot, Nacos, Spring Cloud Alibaba, Kubernetes, Redis, MinIO, AI-assisted generation and real-time collaboration. Compared with a centralized baseline whose average 4K frame rendering time is 31.8 s, the proposed system reduces the time to 12.5 s, lowers the P95 collaborative response time from 2.46 s to 0.91 s and keeps the final unrecovered task error rate at 0.01% in distributed node failure tests. These results show that the proposed scheme improves rendering efficiency, material access and collaboration reliability.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Lili Zhang
AU  - Yixin Pan
AU  - Qingxi Liu
AU  - Jiahui Wang
PY  - 2026
DA  - 2026/08/18
TI  - Research on Optimization of Efficient Animation Video Production Process Driven by Cloud Computing
BT  - Proceedings of the 2026 5th International Conference on Art Design and Digital Technology (ADDT 2026)
PB  - Atlantis Press
SP  - 608
EP  - 615
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-737-8_72
DO  - 10.2991/978-94-6239-737-8_72
ID  - Zhang2026
ER  -