IDSS, a Novel P2P Relational Data Storage Service

The rate at which data is generated has been increasing rapidly, raising challenges related to its management. Traditional database management systems suffer from scalability and are usually inefficient when dealing with large-scale and heterogeneous data. This paper introduces IDSS (InnoCyPES Data Storage Service), a novel large-scale data storage tool that leverages peer-to-peer networks and embedded relational databases. We present the IDSS architecture and its design, and provide details related to the implementation. The peer-to-peer framework is used to provide support for distributed queries leveraging a relational database architecture based on a common schema. Furthermore, methods to support complex distributed query processing, enabling robust and efficient management of vast amounts of data are presented.

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Publication Details

Journal
ArXiv.org
Published
2025-07-19
Primary Topic
Advanced Database Systems and Queries
Type
article
Field-Weighted Citation Impact
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article

IDSS, a Novel P2P Relational Data Storage Service

Hugo Morais, Lucas A. Pereira, Marco Pulimeno, Massimo Cafaro et al.
ArXiv.org
Advanced Database Systems and Queries
article

IDSS, a Novel P2P Relational Data Storage Service

Hugo Morais, Lucas A. Pereira, Marco Pulimeno, Massimo Cafaro, Italo Epicoco, Lunodzo J. Mwinuka
article en

Abstract

The rate at which data is generated has been increasing rapidly, raising challenges related to its management. Traditional database management systems suffer from scalability and are usually inefficient when dealing with large-scale and heterogeneous data. This paper introduces IDSS (InnoCyPES Data Storage Service), a novel large-scale data storage tool that leverages peer-to-peer networks and embedded relational databases. We present the IDSS architecture and its design, and provide details related to the implementation. The peer-to-peer framework is used to provide support for distributed queries leveraging a relational database architecture based on a common schema. Furthermore, methods to support complex distributed query processing, enabling robust and efficient management of vast amounts of data are presented.

ArXiv.org
Openalex Percentile: Top 58%
Advanced Database Systems and Queries
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