TY - GEN
T1 - Self-adaptive Internet of Things Systems
T2 - 5th International Conference on Applied Technologies, ICAT 2023
AU - Erazo Garzón, Lenin Xavier
AU - Gutiérrez, Bayron
AU - Illescas Peña, Lourdes
AU - Bermeo, Alexandra
AU - Erazo Garzón, Lenin Xavier
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - The dynamic and uncertain nature in which IoT systems operate has led to the exploration of new emerging Software Engineering approaches, such as self-adaptation, to provide these systems with autonomous capabilities to adjust their behavior at runtime to environmental changes. There are numerous primary studies on self-adaptation in IoT; however, it is necessary to deepen and update the state of technological knowledge in this area, especially in aspects that have not been addressed in previous reviews. Therefore, this paper presents a systematic review of the literature on self-adaptation in IoT systems, according to the guidelines proposed by Kitchenham et al. and the self-adapting topology created by Krupitzer et al. This review aims to answer the following research questions: i) In what context has self-adaptation been used in the IoT domain? ii) How is self-adaptation performed in IoT platforms? and iii) What is the research approach in studies related to self-adaptive systems in IoT? First, 1136 primary studies were obtained through automatic and manual searches. Then, inclusion and exclusion criteria were applied to select 84 relevant studies on self-adaptation in IoT. Finally, quantitative and qualitative methods based on extraction criteria were used to synthesize the strengths and weaknesses of the studies concerning the research questions as well as to identify research gaps and opportunities
AB - The dynamic and uncertain nature in which IoT systems operate has led to the exploration of new emerging Software Engineering approaches, such as self-adaptation, to provide these systems with autonomous capabilities to adjust their behavior at runtime to environmental changes. There are numerous primary studies on self-adaptation in IoT; however, it is necessary to deepen and update the state of technological knowledge in this area, especially in aspects that have not been addressed in previous reviews. Therefore, this paper presents a systematic review of the literature on self-adaptation in IoT systems, according to the guidelines proposed by Kitchenham et al. and the self-adapting topology created by Krupitzer et al. This review aims to answer the following research questions: i) In what context has self-adaptation been used in the IoT domain? ii) How is self-adaptation performed in IoT platforms? and iii) What is the research approach in studies related to self-adaptive systems in IoT? First, 1136 primary studies were obtained through automatic and manual searches. Then, inclusion and exclusion criteria were applied to select 84 relevant studies on self-adaptation in IoT. Finally, quantitative and qualitative methods based on extraction criteria were used to synthesize the strengths and weaknesses of the studies concerning the research questions as well as to identify research gaps and opportunities
KW - Cyber-physical Systems
KW - Internet of Things (IoT)
KW - Self-adaptation
KW - Software Engineering
KW - Systematic Literature Review
KW - Cyber-physical Systems
KW - Internet of Things (IoT)
KW - Self-adaptation
KW - Software Engineering
KW - Systematic literature review
UR - https://www.scopus.com/pages/publications/85197281009
UR - https://jisajournal.springeropen.com/articles/10.1186/s13174-021-00145-8
U2 - 10.1007/978-3-031-58950-8_11
DO - 10.1007/978-3-031-58950-8_11
M3 - Contribución a la conferencia
AN - SCOPUS:85197281009
SN - 9783031589492
VL - Part III
T3 - Communications in Computer and Information Science
SP - 137
EP - 157
BT - 5th International Conference on Applied Technologies, ICAT 2023
A2 - Botto-Tobar, Miguel
A2 - Zambrano Vizuete, Marcelo
A2 - Montes León, Sergio
A2 - Torres-Carrión, Pablo
A2 - Durakovic, Benjamin
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 22 November 2023 through 24 November 2023
ER -