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Architectural Trends in Collaborative Computing: Approaches in the Internet of Everything Era

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  • Débora Souza

    (Systems Engineering and Computing Program, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-972, Brazil
    These authors contributed equally to this work.)

  • Gabriele Iwashima

    (Systems Engineering and Computing Program, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-972, Brazil
    These authors contributed equally to this work.)

  • Viviane Cunha Farias da Costa

    (Systems Engineering and Computing Program, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-972, Brazil
    Fundação Getulio Vargas (FGV), Rio de Janeiro 22250-145, Brazil)

  • Carlos Eduardo Barbosa

    (Systems Engineering and Computing Program, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-972, Brazil
    Centro de Análises de Sistemas Navais (CASNAV), ICT of the Brazilian Navy, Rio de Janeiro 20091-000, Brazil)

  • Jano Moreira de Souza

    (Systems Engineering and Computing Program, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-972, Brazil)

  • Geraldo Zimbrão

    (Systems Engineering and Computing Program, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-972, Brazil)

Abstract

The majority of the global population now resides in cities, and this trend continues to grow. In this context, the Internet of Things (IoT) is crucial in transforming existing urban areas into Smart Cities. However, IoT architectures mainly focus on machine-to-machine interactions, leaving human involvement aside. The Internet of Everything (IoE) includes human-to-human and human–machine collaboration, but the specifics of these interactions are still under-explored. As urban populations grow and IoT integrates into city infrastructure, efficient, collaborative architectures become crucial. In this work, we use the Rapid Review methodology to analyze collaboration in four prevalent computing architectures in the IoE paradigm, namely Edge Computing, Cloud Computing, Blockchain/Web Services, and Fog Computing. To analyze the collaboration, we use the 3C collaboration model, comprising communication, cooperation, and coordination. Our findings highlight the importance of Edge and Cloud Computing for enhancing collaborative coordination, focusing on efficiency and network optimization. Edge Computing supports real-time, low-latency processing at data sources, while Cloud Computing offers scalable resources for diverse workloads, optimizing coordination and productivity. Effective resource allocation and network configuration in these architectures are essential for cohesive IoT ecosystems. Therefore, this work offers a comparative analysis of four computing architectures, clarifying their capabilities and limitations. Smart Cities are a major beneficiary of these insights. This knowledge can help researchers and practitioners choose the best architecture for IoT and IoE environments. Additionally, by applying the 3C collaboration model, the article provides a framework for improving collaboration in IoT and IoE systems.

Suggested Citation

  • Débora Souza & Gabriele Iwashima & Viviane Cunha Farias da Costa & Carlos Eduardo Barbosa & Jano Moreira de Souza & Geraldo Zimbrão, 2024. "Architectural Trends in Collaborative Computing: Approaches in the Internet of Everything Era," Future Internet, MDPI, vol. 16(12), pages 1-28, November.
  • Handle: RePEc:gam:jftint:v:16:y:2024:i:12:p:445-:d:1532853
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    References listed on IDEAS

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    1. Vítor de Castro Paes & Clinton Hudson Moreira Pessoa & Rodrigo Pereira Pagliusi & Carlos Eduardo Barbosa & Matheus Argôlo & Yuri Oliveira de Lima & Herbert Salazar & Alan Lyra & Jano Moreira de Souza, 2023. "Analyzing the Challenges for Future Smart and Sustainable Cities," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
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