This paper presents a structured algorithmic framework for automated physical design tuning in SQL-based relational databases. The approach centers on an incremental, anytime-capable optimization process that intelligently parses SQL workloads, identifies syntactically relevant and workload-significant table subsets and column groups, and iteratively refines candidate physical design structures including B+-tree indexes, materialized views, and partitioned indexes (conceptual framework support; see Section 4.1 for implementation status). Through a multi-phase methodology involving workload compression, candidate selection, index merging, and greedy enumeration, the system efficiently navigates the configuration space under storage and time constraints. A novel prioritization mechanism ensures early focus on high-impact queries while maintaining the ability to refine recommendations progressively. This SQL-native methodology is fully integrated with the query optimizer's what-if analysis interface (implemented as a prototype extension for PostgreSQL 14, using the HypoPG extension version 1.3.1 for hypothetical index evaluation) and is designed to support large-scale, dynamic workload environments with practical time-bounded tuning scenarios.
Sheshukumar Vangala· International Journal of Int...· 0 citations
This paper presents an information technology-driven bibliometric framework for mapping the structural and temporal evolution of interdisciplinary intellectual linkage and apparent conceptual diffusion within the domain of social network analysis. Utilizing large-scale metadata from Web of Science, we construct multiple bibliometric networks representing citation, co-authorship, and keyword relationships. Through computational methods including fractional normalization, Search Path Count (SPC) edge-weighting, and island detection algorithms, we identify latent communities and bibliometric pathways that suggest patterns of intellectual association and citation-mediated influence between social sciences, physics, neuroscience, and behavioral ecology. These computational outputs represent citation-mediated influence patterns and co-occurrence structures, not direct observation of knowledge transmission. Our results highlight the role of digital libraries and algorithmic normalization in addressing terminological and data-quality challenges, alongside name disambiguation procedures and network pruning to mitigate citation boundary issues. This paper contributes to the domain of information technology by demonstrating scalable computational techniques for uncovering hidden intellectual structures and bibliometric evidence of knowledge flows in an increasingly interdisciplinary research landscape.
Sheshukumar Vangala· International Journal of Int...· 0 citations
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