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The emerging fog computing technology is characterized by an ultralow latency response, which benefits a massive number of time-sensitive services and applications in the Internet of things (IoT) era. To this end, the fog computing infrastructure must minimize latencies for both service delivery and execution phases. While the transmission latency significantly depends on external factors (e.g., channel bandwidth, communication resources, and interferences), the computation latency can be considered as an internal issue that the fog computing infrastructure could actively self-handle. From this view point, we propose a reinforcement learning approach that utilizes the evolution strategies for real-time task assignment among fog servers to minimize the total computation latency during a long-term period. Experimental results demonstrate that the proposed approach reduces the latency by approximately 16.1% compared to the existing methods. Additionally, the proposed learning algorithm has low computational complexity and an effectively parallel operation; therefore, it is especially appropriate to be implemented in modern heterogeneous computing platforms.

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Construction safety education plays a crucial role in improving the safety performance in the construction industry. Many research works have successfully adopted computerized three-dimensional model-based virtual reality (3D-VR) to provide students with adequate safety knowledge and skills before they enter construction sites. Despite the advantages of improving learning outcomes, 3D-VR has limitations not only in reflecting real-world visibility but also in consuming significant energy and requiring strict user-device compatibility. Therefore, this research methodology was initiated with a thorough investigation of VR application in construction safety education. On the basis of a literature review, the study subsequently analyzes the energy-consumption problems of conventional VR systems. Initial findings motivate the development of an energy-efficient learning system (the interactive constructive safety education (eCSE)) using Web-based panoramic virtual photoreality technology for interactive construction safety education. The eCSE system provides three key interactive modules, namely, lesson delivery (LD), practical experience (PE), and knowledge assessment (KA), for use in mobile devices. The trial system has been developed and validated through scenarios derived from real construction sites. The preliminary evaluation reveals that the eCSE system not only overcomes the 3D-VR limitations in terms of energy efficiency, user device adaptability, and easy implementation, but also improves learning usability.