Pattern-Based Architecture for Adaptive Multimedia Processing in Heterogeneous Environments: A Modular Approach with UML Modeling
DOI:
https://doi.org/10.64229/kp9vj408Keywords:
Multimedia patterns, Software Architecture, Design Reuse, Adaptive Streaming, UML Modeling, Real-time SystemsAbstract
Multimedia systems increasingly operate across heterogeneous devices and fluctuating network conditions, requiring adaptable and modular architectures to ensure real-time performance and cross-platform compatibility. Traditional multimedia frameworks such as FFmpeg and GStreamer, though powerful, often suffer from tightly coupled designs that limit reuse and dynamic reconfiguration. This paper addresses these limitations by introducing a set of reusable Multimedia Design Patterns tailored to the challenges of adaptive video processing, codec interoperability, and system heterogeneity.
The proposed framework is grounded in pattern-based architectural modeling and formalized using UML class and component diagrams. Key patterns include the Stream Handler Pattern, Adaptive Codec Selector, Filter Chain, and Media Buffer Pattern—each designed to abstract core multimedia tasks such as input/output management, codec switching, filter composition, and buffer synchronization.
To validate the effectiveness of these patterns, we implement a real-time cross-platform video streaming client that dynamically adjusts its encoding strategy and processing pipeline based on runtime conditions. The case study demonstrates how pattern-driven modularization improves reusability, reduces latency, and enables runtime pipeline reconfiguration with minimal code dependencies.
Performance evaluation compares the pattern-based solution to a monolithic baseline using metrics such as frame processing time, resource consumption, and switching delay. Results show up to 38% improvement in responsiveness and 29% reduction in memory overhead.
This work contributes a practical, scalable approach to multimedia system design, supporting both academic advancement and industrial deployment in smart streaming, edge rendering, and IoT media delivery contexts.
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