Title: Communication algorithm of parallel database HPDB system based on computer intelligent network and data integration

Authors: Zhenhua Dai; Tingting Wu; Jun Li

Addresses: School of Information Engineering, Hunan University of Science and Engineering, Yongzhou 425199, Hunan, China ' Shandong Vocational College of Science and Technology, No. 6388 Xihuan Road, Weifang 261053, Shandong, China ' Shandong Vocational College of Economics and Trade, No. 2799 Qingnian Road, Weicheng District, Weifang 261011, Shandong, China

Abstract: Traditional database systems are replaced with high-performance parallel databases with intricate and time-consuming querying and data processing demands. As the need exists for processing queries in multiple distinct relations, the database systems are ideally suited for parallel execution. This paper proposes an AINF-HPDB system designed for a parallel high-performance database (HPDB) system using adaptive intent-based network framework (AINF) computer intelligence architecture. The suggested approach utilises flexible and innovative capabilities to optimise communication interactions within the parallel HPDB system. The proposed idea aims to maximise throughput in the operation of the parallel database system, minimise latency, and utilise the intelligence and adaptability of network components to improve data transfer efficiency. To maximise performance and efficiency during large dataset handling across various sectors, the proposed idea finds application in the financial services industry for trading at high frequencies, telecommunications for managing networks, scientific studies for simulations, and internet of things for data-intensive applications.

Keywords: high-performance database system; computer intelligent network; adaptive intent-based networking framework; adaptive routing; load balancing.

DOI: 10.1504/IJIIDS.2025.147423

International Journal of Intelligent Information and Database Systems, 2025 Vol.17 No.3/4, pp.477 - 497

Received: 28 Feb 2024
Accepted: 26 Jun 2024
Published online: 15 Jul 2025 *

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