Abstract
Managing and accessing data in distributed computing environments presents several challenges that traditional techniques often fail to address efficiently and adaptively. In distributed computing environments, data is replicated across various locations to ensure availability and performance. However, this has several drawbacks including high costs, complexity in data management, inefficient resource utilization, use of static data access strategies, high latency, etc. Data virtualization, data federation, distributed file systems, etc. do not provide responsive data storage that is dynamically updated based on real-time usage patterns and that can help reduce data storage costs. This disclosure describes a dynamic framework that integrates context-aware caching with symbolic links. The described approach allows for real-time adaptation to various contextual factors, optimizing data access paths, reducing unnecessary data replication, and enhancing overall system efficiency and user experience. The described techniques present an innovative approach to data management in distributed systems, enhancing adaptability, efficiency, and user experience.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Mahajan, Puneet, "Dynamic Data Access Framework Using Symbolic Links and Context-Aware Caching", Technical Disclosure Commons, (May 30, 2024)
https://www.tdcommons.org/dpubs_series/7057