Multi-Step Reasoning for IoT Devices
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Article in Proceedings |
| Conference | Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2023) |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.5220/0011772700003464 |
| Keywords | Internet of Things (IoT); Web of Things (WoT); Semantic Reasoning |
| Description | Internet of Things (IoT) devices are constantly growing in numbers, forecasted to reach 27 billion in 2025. With such a large number of connected devices, energy consumption concerns are a major priority for the upcoming years. Cloud / Edge / Fog Computing are critically associated with IoT devices as enablers for data communication and coordination among devices. In this paper, we look at the distribution of Semantic Reasoning between IoT devices and define a new class of reasoning, multi-step reasoning, that can be associated at the level of the edge or fog node in the context of IoT devices. We conduct an experiment based on synthetic datasets to evaluate the performance of multi-step reasoning in terms of power consumption, memory, and CPU usage. Overall we found that multi-step reasoning can help in reducing computation time and energy consumption on IoT devices in the presence of larger datasets. |
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