Characterizing time-critical internet of things

The Internet of Things (IoT) is increasingly being adopted in diverse domains, many of which require strict timing constraints and predictable behavior. Despite the growing importance of timing characteristics in IoT applications, current approaches to address timing requirements are often fragmented, context-specific, and lack a unified understanding. Consequently, addressing timing aspects in IoT remains largely ad hoc and dependent on individual applications, making it challenging to generalize findings or systematically apply established solutions. The goal of this study is to provide a comprehensive understanding of how timing is defined, characterized, and measured within the IoT community. We conducted this study through a systematic and structured mix methods research approach. First, we performed a systematic review of the literature, extracting and analyzing information from 38 primary studies, selected from a rigorous process involving 1176 studies. Second, to complement the literature findings, we conducted an expert survey involving 28 respondents from academia and industry, representing a variety of roles with specialized expertise in IoT systems and timing-related issues. We identified two primary characterizations of timing within the IoT: time-criticality and predictability. Additionally, we collected and categorized 113 distinct timing metrics from literature into commonly found layers of an IoT system. The majority of the surveyed practitioners and researchers (75%) agree with our categorization and consider this research useful and relevant (71.5%). We believe that our study provides practitioners and researchers with insights into timing characteristics and metrics in IoT applications, toward the ultimate goal of standardization. • Systematic review of 38 studies on timing in IoT selected from 1176 publications. • Defined key timing concepts in IoT: predictability, time-criticality. • Extracted 113 timing metrics, categorized by architecture layers and types. • Expert survey complements literature on timing challenges in IoT systems.

Authors

Institutions

Publication Details

Journal
Internet of Things
Published
2025-08-26
DOI
https://doi.org/10.1016/j.iot.2025.101721
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterizing time-critical internet of things

Mohammad Ashjaei, Alessio Bucaioni, Sebastian Leclerc
Internet of Things
IoT and Edge/Fog Computing
article

Characterizing time-critical internet of things

Mohammad Ashjaei, Alessio Bucaioni, Sebastian Leclerc
article en

Abstract

The Internet of Things (IoT) is increasingly being adopted in diverse domains, many of which require strict timing constraints and predictable behavior. Despite the growing importance of timing characteristics in IoT applications, current approaches to address timing requirements are often fragmented, context-specific, and lack a unified understanding. Consequently, addressing timing aspects in IoT remains largely ad hoc and dependent on individual applications, making it challenging to generalize findings or systematically apply established solutions. The goal of this study is to provide a comprehensive understanding of how timing is defined, characterized, and measured within the IoT community. We conducted this study through a systematic and structured mix methods research approach. First, we performed a systematic review of the literature, extracting and analyzing information from 38 primary studies, selected from a rigorous process involving 1176 studies. Second, to complement the literature findings, we conducted an expert survey involving 28 respondents from academia and industry, representing a variety of roles with specialized expertise in IoT systems and timing-related issues. We identified two primary characterizations of timing within the IoT: time-criticality and predictability. Additionally, we collected and categorized 113 distinct timing metrics from literature into commonly found layers of an IoT system. The majority of the surveyed practitioners and researchers (75%) agree with our categorization and consider this research useful and relevant (71.5%). We believe that our study provides practitioners and researchers with insights into timing characteristics and metrics in IoT applications, toward the ultimate goal of standardization. • Systematic review of 38 studies on timing in IoT selected from 1176 publications. • Defined key timing concepts in IoT: predictability, time-criticality. • Extracted 113 timing metrics, categorized by architecture layers and types. • Expert survey complements literature on timing challenges in IoT systems.

Internet of ThingsVol. 34
Mälardalen University (SE)
VINNOVA
Openalex Percentile: Top 75%
IoT and Edge/Fog Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Characterizing time-critical internet of things — Mohammad Ashjaei, Alessio Bucaioni, et al. · Internet of Things (2025) | TGRS Research Map | TGRS