Abstract
The Internet of Robotic Things (IoRT) has emerged as a promising computing paradigm integrating the cloud/fog/edge computing continuum in the Internet of Things (IoT) to optimize the operations of intelligent robotic agents in factories. A single robot agent at the edge of the network can comprise hundreds of sensors and actuators; thus, the tasks performed by multiple agents can be computationally expensive, which are often possible by offloading the computing tasks to the distant computing resources in the cloud or fog computing layers. In this context, it is of paramount importance to assimilate the performance impact of different system components and parameters in an IoRT infrastructure to provide IoRT system designers with tools to assess the performance of their manufacturing projects at different stages of development. Therefore, we propose in this article a performance evaluation methodology based on the D/M/c/K/FCFS queuing network pattern and present a queuing-network-based performance model for the performance assessment of compatible IoRT systems associated with the edge, fog, and cloud computing paradigms. To find the factors that expose the highest impact on the system performance in practical scenarios, a sensitivity analysis using the Design of Experiments (DoE) was performed on the proposed performance model. On the outputs obtained by the DoE, comprehensive performance analyses were conducted to assimilate the impact of different routing strategies and the variation in the capacity of the system components. The analysis results indicated that the proposed model enables the evaluation of how different configurations of the components of the IoRT architecture impact the system performance through different performance metrics of interest including the (i) mean response time, (ii) utilization of components, (iii) number of messages, and (iv) drop rate. This study can help improve the operation and management of IoRT infrastructures associated with the cloud/fog/edge computing continuum in practice.
Highlights
The Internet of Robotic Things (IoRT) adopts the advanced computing capabilities and features of the fog and cloud computing paradigms, such as (i) virtualization technologies, (ii) layered services, and (iii) the agile provisioning capabilities of local/remote computing resources, while integrating into the Internet of Things (IoT) infrastructure associated with its enabling technologies to make the design and implementation of new applications more flexible for the robotic manufacturing systems [3]
This study extends current progress in previous works by performing a comprehensive sensitivity analysis based on the Design of Experiments (DoE) to find the factors that expose the highest impact on the system performance, adopting the obtained values of these factors in the performance model in different practical scenarios for performance evaluation
A higher weight with a low capacity selected for a specific computing layer can lead to significant package losses of messages; When comparing the results by the computing layers in the three specific scenarios, it was observed that the fog had the lowest Mean Response Time (MRT), which as smaller than the private cloud, which in turn had a lower MRT than the public cloud
Summary
The Internet of Robotic Things (IoRT) is an emerging computing paradigm for robotic systems in factories, which is expected to revolutionize the whole manufacturing industry [1,2]. The IoRT adopts the advanced computing capabilities and features of the fog and cloud computing paradigms, such as (i) virtualization technologies, (ii) layered services, and (iii) the agile provisioning capabilities of local/remote computing resources, while integrating into the Internet of Things (IoT) infrastructure associated with its enabling technologies (e.g., sensors and actuators embedded in smart devices) to make the design and implementation of new applications more flexible for the robotic manufacturing systems [3]. The IoRT is considered as the evolution of cloud robotics [4], by integrating the IoT to leverage and expand the use of robots in industry. The IoT is considered one of the top five trends in recent years [5]
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