The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application
Abstract
Wireless sensor networks (WSNs) groups specialized transducers that provide sensing services to Internet of Things (IoT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important role in power conservation for the energy constrained network. Choosing a cluster head (CH) can appropriately balance the load in the network thereby reducing energy consumption and enhancing lifetime. This paper focuses on an efficient CH election scheme that rotates the CH position among the nodes with higher energy level as compared to other. The algorithm considers initial energy, residual energy, and an optimum value of CHs to elect the next group of CHs for the network that suits for IoT applications, such as environmental monitoring, smart cities, and systems. Simulation analysis shows the modified version performs better than the low energy adaptive clustering hierarchy protocol by enhancing the throughput by 60%, lifetime by 66%, and residual energy by 64%.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Energy-efficient communication protocol for wireless microsensor networks
Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2005) · Proceedings of the 33rd Annual Hawaii International Conference on System Sciences · doi:10.1109/hicss.2000.926982 · Cited by 14,140
Internet of Things (IoT): A vision, architectural elements, and future directions
Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013) · Future Generation Computer Systems · doi:10.1016/j.future.2013.01.010 · Cited by 12,293
An application-specific protocol architecture for wireless microsensor networks
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2002.804190 · Cited by 10,565
Research Directions for the Internet of Things
Stankovic, J. A. (2014) · IEEE Internet of Things Journal · doi:10.1109/jiot.2014.2312291 · Cited by 1,920
Internet of Things: Applications and Challenges in Technology and Standardization
Bandyopadhyay, D., & Sen, J. (2011) · Wireless Personal Communications · doi:10.1007/s11277-011-0288-5 · Cited by 1,507
An Information Framework for Creating a Smart City Through Internet of Things
Jin, J., Gubbi, J., Marusic, S., & Palaniswami, M. (2014) · IEEE Internet of Things Journal · doi:10.1109/jiot.2013.2296516 · Cited by 1,320
Security of the Internet of Things: perspectives and challenges
Jing, Q., Vasilakos, A. V., Wan, J., Lu, J., & Qiu, D. (2014) · Wireless Networks · doi:10.1007/s11276-014-0761-7 · Cited by 1,245
Future internet: The Internet of Things
Tan, L., & Wang, N. (2010) · 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE) · doi:10.1109/icacte.2010.5579543 · Cited by 833
Improvement on LEACH Protocol of Wireless Sensor Network
Xiangning, F., & Yulin, S. (2007) · International Conference on Sensor Technologies and Applications · doi:10.1109/sensorcomm.2007.4394931 · Cited by 572
Rao, P. C. S., Jana, P. K., & Banka, H. (2016) · Wireless Networks · doi:10.1007/s11276-016-1270-7 · Cited by 438
Cited by
SmartBlock-SDN: An Optimized Blockchain-SDN Framework for Resource Management in IoT
Rahman, A., Islam, M. J., Montieri, A., Nasir, M. K., Reza, M. M., Band, S. S., Pescape, A., Hasan, M., Sookhak, M., & Mosavi, A. (2021) · IEEE Access · doi:10.1109/access.2021.3058244 · Cited by 187
DistB-Condo: Distributed Blockchain-Based IoT-SDN Model for Smart Condominium
Rahman, A., Islam, M. J., Rahman, Z., Reza, M. M., Anwar, A., Mahmud, M. A. P., Nasir, M. K., & Noor, R. M. (2020) · IEEE Access · doi:10.1109/access.2020.3039113 · Cited by 66
Asaithambi, S., Ravi, L., Kotb, H., Milyani, A. H., Azhari, A. A., Nallusamy, S., Varadarajan, V., & Vairavasundaram, S. (2022) · Sensors · doi:10.3390/s22207917 · Cited by 41
Metadata
- Authors
- Behera, T. M., Mohapatra, S. K., Samal, U. C., Khan, M. S., Daneshmand, M., & Gandomi, A. H.
- Venue
- IEEE Internet of Things Journal
- Published
- 2019-06
- Volume
- 6
- Issue
- 3
- Pages
- 5132-5139
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W2913300069
- Cited by
- 489
- References
- 21
- FWCI
- 38.83
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application. https://app.cochat.ai/papers/10.1109/jiot.2019.2897119
- The paper
- Behera, T. M., Mohapatra, S. K., Samal, U. C., Khan, M. S., Daneshmand, M., & Gandomi, A. H. (2019). Residual Energy-Based Cluster-Head Selection in WSNs for IoT Application. IEEE Internet of Things Journal. https://doi.org/10.1109/jiot.2019.2897119
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
