A Kotlin multi-platform implementation of aggregate computing based on XC

Cortecchia, Angela (2024) A Kotlin multi-platform implementation of aggregate computing based on XC. [Laurea magistrale], Università di Bologna, Corso di Studio in Ingegneria e scienze informatiche [LM-DM270] - Cesena
Documenti full-text disponibili:
[img] Documento PDF (Thesis)
Disponibile con Licenza: Creative Commons: Attribuzione - Non commerciale - Condividi allo stesso modo 4.0 (CC BY-NC-SA 4.0)

Download (3MB)

Abstract

The integration of technology in everyday activities is rising, with objects being increasingly equipped with computational capabilities and interconnected to form the Internet of Things, leading to the need for innovative cyber-physical services capable of creating a fast bridge between the real and virtual world. The central idea of this thesis focuses on leveraging Kotlin Multiplatform to enhance aggregate computing based on XC principles, addressing challenges in developing versatile solutions across different environments, with the need of efficient and scalable applications operating from cloud to edge to mesh networks. This thesis combines theoretical analysis, software development, and performance evaluation to assess the effectiveness of the objective, demonstrating versatility and efficiency. There is a notable improvement in performance, scalability, and adaptability across different network environments. With the proposed approach, the developed solution appears to be more efficient and effective in addressing complex challenges within systems rather than the current state of the art. The results demonstrate the transformative potential of this technology, suggesting that it can lead to more efficient and versatile service development. In summary, this thesis shows the feasibility of using Kotlin Multiplatform to implement aggregate computing based on XC, demonstrating that the proposed approach is more efficient and scalable than the state of the art. Improved performance and scalability are emphasised through this approach, which opens doors for more efficient and adaptable solutions. This study sets the stage for future developments that could improve service efficiency and effectiveness.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Cortecchia, Angela
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
aggregate computing,kotlin,xc
Data di discussione della Tesi
15 Marzo 2024
URI

Altri metadati

Statistica sui download

Gestione del documento: Visualizza il documento

^