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Hybrid P2P-Based Architecture for Remote Software Utilization.

Authors :
Baaziz, Abdelhalim
Achache, Abir
Source :
Revue d'Intelligence Artificielle; Apr2024, Vol. 38 Issue 2, p631-641, 11p
Publication Year :
2024

Abstract

The world presents us with two contradictory situations. Firstly, most people encounter the problem of lacking necessary hardware and/or software resources. Secondly, some individuals or organizations possess these resources but fail to utilize them to their full potential. The proposed solution is to provide underutilized resources to those who require them. However, it is important to ensure that there is no illegal copying or pirating of software. Instead, the owners of these resources can offer their services by processing data remotely. The Peer-to-peer (P2P) paradigm is used primarily for collaborative systems over a network. This article proposes a Hybrid P2P-Based collaborative architecture that employs HTTP transport to provide data remote-treatment services. In our peer-to-peer (P2P) solution, one peer provides a service, such as a software application capable of processing specific data, while another peer actively searches for this software and sends its own data to be processed by it. In this scenario, the second peer can utilize the software without encountering piracy issues, given that the first peer executes the software locally and adheres to the appropriate license. By employing HTTP for communication, it enables collaborative interaction among heterogeneous peer platforms. This system enables individuals without essential hardware and/or software resources to leverage the resources provided by others. The simulation results conducted using PeerSim simulator, are encouraging, indicating that the proposed architecture can serve as a reliable solution for collaboration between peers. The outcomes of the simulation demonstrate a significant level of satisfaction across the essential metrics we defined to assess the effectiveness of our solution. particularly in terms of responsiveness to requests, resulting in approximately 80% satisfaction and 20% dissatisfaction rates for requests. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0992499X
Volume :
38
Issue :
2
Database :
Complementary Index
Journal :
Revue d'Intelligence Artificielle
Publication Type :
Academic Journal
Accession number :
177097248
Full Text :
https://doi.org/10.18280/ria.380227