Reducing communication overhead in the IoT–edge–cloud continuum: A survey on protocols and data reduction strategies

Abstract

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 with IoT services in the IoT–edge–cloud continuum. This increase in network traffic 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 size of 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 explore various data traffic reduction techniques tailored to the IoT–edge–cloud context and evaluate their applicability and effectiveness on resource-constrained end devices. Finally, we investigate the emerging concepts that have the potential to further reduce 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.