ACS Applied Computer Science

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The Internet of Things (IoT) touches almost every aspect of modern society and has changed the way people live, work, travel and, do business. Because of its importance, it is essential to ensure that an IoT system is performing well, as desired and expected, and that this can be assessed and managed with an adequate set of IoT performance metrics. The aim of this study is to systematically inventory and classify recent studies that have investigated IoT metrics. The authors conducted a literature review based on studies published between January 2010 and December 2021 using a set of five research questions (RQs) on the current knowledge bases for IoT metrics. A total of 158 IoT metrics were identified and classified into 12 categories according to the different parts and aspects of an IoT system. To cover the overall performance of an IoT system, the 12 categories were organized into an ontology. The results show that the category of network metrics was most frequently discussed in 43% of the studies and, with the highest number of metrics at 37%. This study can provide guidelines for researchers and practitioners in selecting metrics for IoT systems and valuable insights into areas for improvement and optimization.

  • APA 7th style
Moulla, D. K., Mnkandla, E., & Abran, A. (2023). Systematic literature review of IoT metrics. Applied Computer Science, 19(1), 64-81.
  • Chicago style
Moulla, Donatien Koulla, Ernest Mnkandla, and Alain Abran. "Systematic literature review of IoT metrics. Applied Computer Science." Applied Computer Science 19, no. 1 (2023): 64-81. 
  • IEEE style
D.K. Moulla, E. Mnkandla, and A. Abran, "Systematic literature review of IoT metrics. Applied Computer Science," Applied Computer Science, vol. 19, no. 1, pp.64-81, 2023, doi: 10.35784/acs-2023-05.
  • Vancouver style
Moulla D.K, Mnkandla E, Abran A. Systematic literature review of IoT metrics. Applied Computer Science. Applied Computer Science. 2023;19(1):64-81.