A Survey of DDS Implementation in Edge and Fog Computing

Abstract

This survey investigates the application of the Data Distribution Service (DDS) within the domains of edge and fog computing architectures. DDS, a middleware architecture conceived by the Object Management Group (OMG), offers robust publish-subscribe functionalities characterized by low latency, high reliability, and scalability attributes, rendering it particularly suitable for real-time data dissemination in distributed systems. The paradigms of edge and fog computing, recognized for their capability to process data in proximity to its origin, leverage the functionalities of DDS to tackle issues such as latency minimization, bandwidth enhancement, and resource efficiency. The research meticulously evaluates the significance of DDS in facilitating scalable and reliable communication for applications spanning industrial automation, healthcare, and smart urban environments. It delineates pivotal implementation obstacles, including resource limitations, interoperability challenges, and security concerns within decentralized frameworks. Mitigation strategies such as lightweight DDS protocols, adaptive Quality of Service (QoS) policies, and artificial intelligence-driven optimizations are underscored to address these constraints. Employing PRISMA guidelines, a total of 16 peer-reviewed studies were scrutinized to respond to research inquiries centered on the role of DDS in edge and fog computing, associated technical hurdles, implications for QoS, and emergent trends. The results underscore the capacity of DDS to converge with cutting-edge tech-nologies such as 5G, blockchain, and digital twins, thereby influencing the evolution of intelligent distributed systems. This survey enhances the existing comprehension of DDS's transformative capabilities within contemporary computing architectures, offering valuable insights into best practices and prospective avenues for the optimization of edge and fog computing environments.