Experimental Analysis of Energy Efficient and QoS Aware Objective Functions for RPL Algorithm in IoT Networks
Abstract
Keywords
References
- I. M. Shehabat and N. Al-Hussein, “Deploying internet of things in healthcare: Benefits, requirements, challenges and applications,” J. Commun., pp. 574–580, 2018.
- M. R. Palattella, N. Accettura, X. Vilajosana, T. Watteyne, L. A. Grieco, G. Boggia, & M. Dohler. Standardized protocol stack for the internet of (important) things. IEEE Communications Surveys Tutorials, 15(3):1389–1406, 2013.
- N. Benamar, A. Jara, L. Ladid, and D. E. Ouadghiri, “Challenges of the internet of things: IPv6 and network management,” 2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, pp. 328–333, 2014.
- E. Borgia, “The Internet of Things vision: Key features, applications and open issues,” Comput. Commun., vol. 54, pp. 1–31, 2014.
- J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Comput. netw., vol. 52, no. 12, pp. 2292–2330, 2008.
- L. Atzori, A. Iera, and G. Morabito. Th e internet of things: A survey. Computer Networks, 54(15):2787 – 2805, 2010.
- Y. Shin and S. Seol, “Improvement of power consumption in RPL-based networks for mobility environment,” 2020 International Conference on Electronics, Information, and Communication (ICEIC), pp. 1–3, 2020.
- F. Arat and S. Demirci, “Energy and QoS aware analysis and classification of routing protocols for IoT and WSN,” 2020 7th International Conference on Electrical and Electronics Engineering (ICEEE), pp. 221–225, 2020.
Details
Primary Language
English
Subjects
Computer Software
Journal Section
Research Article
Publication Date
August 31, 2021
Submission Date
February 5, 2021
Acceptance Date
June 11, 2021
Published in Issue
Year 2021 Volume: 4 Number: 2
Cited By
Estimation of Uplink Channels for Multiple Users Using Tensor Modeling in RIS-Aided MISO Communication
Sakarya University Journal of Computer and Information Sciences
https://doi.org/10.35377/saucis...1356872Federated Learning-Based Parent Selection in Low Power and Lossy Networks to Enhance Energy Efficiency
IEEE Open Journal of the Communications Society
https://doi.org/10.1109/OJCOMS.2025.3639481
