The adoption of the Internet of Things (IoT) deployments has led to a sharp increase in network traffic as a vast number of IoT devices communicate with each other and IoT services through the IoT-edge-cloud continuum. This network traffic increase poses a major challenge to the global communications infrastructure since it hinders communication performance and also puts significant strain on the energy consumption of IoT devices. To address these issues, efficient and collaborative IoT solutions which enable information exchange while reducing the transmitted data and associated network traffic are crucial. This survey provides a comprehensive overview of the communication technologies and protocols as well as data reduction strategies that contribute to this goal. First, we present a comparative analysis of prevalent communication technologies in the IoT domain, highlighting their unique characteristics and exploring the potential for protocol composition and joint usage to enhance overall communication efficiency within the IoT-edge-cloud continuum. Next, we investigate various data traffic reduction techniques tailored to the IoT-edge-cloud context and evaluate their applicability and effectiveness on resource-constrained and devices. Finally, we investigate the emerging concepts that have the potential to further reduce the communication overhead in the IoT-edge-cloud continuum, including cross-layer optimization strategies and Edge AI techniques for IoT data reduction. The paper offers a comprehensive roadmap for developing efficient and scalable solutions across the layers of the IoT-edge-cloud continuum that are beneficial for real-time processing to alleviate network congestion in complex IoT environments.

翻译：物联网（IoT）部署的广泛应用导致网络流量急剧增加，大量物联网设备通过物联网-边缘-云连续体相互通信并与物联网服务交互。这种网络流量的增长对全球通信基础设施构成了重大挑战，不仅阻碍通信性能，还对物联网设备的能耗造成巨大压力。为解决这些问题，亟需开发高效协同的物联网解决方案，在实现信息交换的同时减少传输数据量及相关网络流量。本综述系统梳理了有助于实现该目标的通信技术、协议以及数据缩减策略。首先，我们对物联网领域主流通信技术进行比较分析，阐明其独特特性，并探讨协议组合与协同使用的潜力，以提升物联网-边缘-云连续体内的整体通信效率。其次，我们研究了适用于物联网-边缘-云场景的多种数据流量缩减技术，并评估其在资源受限设备上的适用性与有效性。最后，我们探讨了有望进一步降低物联网-边缘-云连续体通信开销的新兴技术，包括跨层优化策略和用于物联网数据缩减的边缘人工智能技术。本文为开发跨物联网-边缘-云连续体各层的高效可扩展解决方案提供了全面路线图，这些方案有利于通过实时处理缓解复杂物联网环境中的网络拥塞问题。