International Journal of Advanced Science and Engineering Research
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e-ISSN 2455-9288
alameenpublications@gmail.com
e-ISSN 2455-9288
ijaser
IJASER publishes high-quality, original research papers, brief reports, and critical reviews in all theoretical, technological, and interdisciplinary studies that make up the fields of advanced science and engineering and its applications.
In the era of big data, extracting valuable insights from vast, distributed, and heterogeneous data sources has become a critical challenge. Distributed Data Mining (DDM) addresses this by enabling mining across decentralized data repositories without centralizing data. However, DDM faces limitations related to scalability, coordination, and real-time adaptability. This paper proposes an enhanced approach to distributed data mining using Multi-Agent Systems (MAS). MAS, composed of intelligent, autonomous agents capable of collaboration and negotiation, provides a robust framework for scalable and flexible data mining operations. By distributing data mining tasks among cooperative agents, the system achieves improved performance, fault tolerance, and adaptability. This hybrid approach enables real-time analysis, minimizes data transfer, and leverages the computational capabilities of distributed environments. The paper discusses the architecture, agent roles, communication protocols, and case studies demonstrating enhanced performance over traditional DDM systems.