# Architectural Trends in Collaborative Computing: Approaches in the Internet of Everything Era
## 6 Conclusions  
The IoE integrates various technologies such as the IoT, Cloud Computing, Big Data, and Data Analytics to create a network of interconnected devices and systems through the Internet. However, IoE necessitates reassessing how collaborative computing architectures integrate smart devices to foster collaboration. Employing a Rapid Review approach to scrutinize selected studies uncovered how these architectures enhance real-time communication, scalability, distributed processing, and security in IoE applications. We summarize the main findings of this work. Answering the first research question, the architectural designs are more focused on collaboration through coordination, aiming to organize collaboration to maximize productivity and reduce operational resources while enhancing the relationship network among collaborators. Answering the second research question, the main adaptations and techniques that need to be integrated into these architectures to boost collaboration are diverse. They must be tailored to different architectural groups. In Edge Computing, the focus is on decentralizing decision-making and enhancing real-time data processing. Cloud Computing emphasizes scalable resources and a robust Application Programming Interface (API) for broader collaboration. Fog Computing targets efficient data flow and advanced networking for real-time decision-making. The Web Services architecture prioritizes interoperable APIs and security for seamless application integration. The Blockchain architecture seeks to ensure trust, transparency, and secure collaboration through consensus mechanisms and smart contracts. Moreover, our main findings include that the Edge and Cloud Computing architectures are highly relevant for collaborative coordination, particularly emphasizing efficiency and network aspects. Efficiency optimization in coordination aims to maximize productivity and operational efficiency by allocating resources effectively and configuring collaborative networks. Edge Computing enables immediate data processing near the source, reducing latency, while Cloud Computing offers scalable resources for handling diverse workloads, optimizing overall efficiency. Finally, network configuration is crucial for seamless communication between devices and servers, fostering cohesive IoT ecosystems and efficient collaboration. Ultimately, understanding and leveraging efficiency and network considerations in Edge and Cloud Computing is essential for developing robust solutions to meet the evolving demands of modern computing paradigms, especially in IoT environments. This work contributes to emerging technologies and Smart Cities through several key avenues. First, we provide a comprehensive comparative analysis of four prevalent computing architectures--Edge Computing, Cloud Computing, Blockchain/Web Services, and Fog Computing--offering a clearer understanding of their unique capabilities and limitations. This analysis can guide researchers and practitioners in selecting the most suitable architecture for specific needs in IoT and IoE environments. Second, by applying the 3C collaboration model (communication, coordination, and cooperation) to these architectures, the article presents a structured framework for evaluating and enhancing collaborative dynamics in IoT systems. Finally, integrating IoT and AI in transforming urban areas into Smart Cities is underscored, highlighting how different architectures can support this transformation, thus contributing to advancing technologies that enable decentralized production control, efficient remote work, enhanced security, and reduced business costs. Nevertheless, the limited number of articles selected highlights the challenge of definitively affirming the comprehensive effectiveness and applicability of the relationship between architectural computing and collaboration.