Dynamic ReLab: A Binary Path-Based Labeling Scheme for Dynamic XML Data

Abstract

Dynamic updates in XML data present significant challenges for maintaining efficient query performance, particularly in large-scale and dynamic environments. Existing labeling schemes, such as ReLab, Dietz encoding, and region numbering, fail to address these challenges effectively due to their reliance on re-labeling entire subtrees during updates, leading to significant computational and memory overhead. These limitations hinder their applicability in dynamic scenarios where frequent updates are required. This study introduces Dynamic ReLab, a novel binary path-based labeling scheme explicitly designed to overcome the inefficiencies of traditional approaches in handling dynamic XML data. By integrating binary path encoding with subtree-based labeling, Dynamic ReLab enables efficient label generation and maintenance, ensuring the quick determination of structural relationships, such as ancestor-descendant and parent-child, without extensive re-labeling. The proposed scheme is particularly advantageous in scenarios where XML data undergo frequent updates, as it significantly reduces the time and memory required for label maintenance, thereby improving overall performance. Experimental results on real-world XML datasets demonstrate that although Dynamic ReLab incurs higher overhead during initial label generation, it substantially outperforms traditional schemes in update processing efficiency. This improvement is achieved through innovative techniques, such as hierarchical bit-masking and binary path concatenation, which streamline the update process and ensure the integrity of the XML structure. These results highlight Dynamic ReLab’s relevance for modern applications requiring real-time adaptability and high-performance query processing in dynamic XML data environments