Efficient Clustering Based Routing for Energy Management in Wireless Sensor Network-Assisted Internet of Things Article Swipe
Sadia Firdous
,
Nargis Bibi
,
Madiha Wahid
,
Samah Alhazmi
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/electronics11233922
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/electronics11233922
Wireless sensor networks (WSNs) play a huge part in arising innovations like smart applications, the Internet of Things, and numerous self-designed, independent applications. Energy exhaustion and efficient energy consumption are principal issues in wireless sensor networks. Energy is a significant and valuable asset of sensor nodes; early energy depletion ultimately leads to a shorter network lifetime and the replacement of sensor nodes. This research proposes a novel Power-Efficient Cluster-based Routing (PECR) algorithm. It takes in clustering using K-Means, the arrangement of Cluster Heads (CHs) and a Main Cluster Head (MCH), the optimal route choice, communication in light of the energy utilization model, cluster heads, and main cluster head alternation based on residual energy and relative location. PECR decreases traffic overburden, restricts energy usage, and at last, expands the network lifetime. Sensor nodes sense the information and transmit traffic to a Base Station (BS) through a legitimate channel. The results confirm it decreases the traffic overhead and effectively utilizes the energy assets. The simulation results show that PECR’s performance is 44% more improved than LEACH, EC, EECRP, and EECA algorithms. It is suitable for networks that require a stretched life.
Related Topics
Concepts
Wireless sensor network
Computer network
Computer science
Base station
Energy consumption
Cluster analysis
Routing protocol
Efficient energy use
Key distribution in wireless sensor networks
Mobile wireless sensor network
Overhead (engineering)
Routing (electronic design automation)
Wireless
Wireless network
Engineering
Telecommunications
Electrical engineering
Machine learning
Operating system
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/electronics11233922
- https://www.mdpi.com/2079-9292/11/23/3922/pdf?version=1669600647
- OA Status
- gold
- Cited By
- 29
- References
- 38
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4310034890
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4310034890Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/electronics11233922Digital Object Identifier
- Title
-
Efficient Clustering Based Routing for Energy Management in Wireless Sensor Network-Assisted Internet of ThingsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-27Full publication date if available
- Authors
-
Sadia Firdous, Nargis Bibi, Madiha Wahid, Samah AlhazmiList of authors in order
- Landing page
-
https://doi.org/10.3390/electronics11233922Publisher landing page
- PDF URL
-
https://www.mdpi.com/2079-9292/11/23/3922/pdf?version=1669600647Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2079-9292/11/23/3922/pdf?version=1669600647Direct OA link when available
- Concepts
-
Wireless sensor network, Computer network, Computer science, Base station, Energy consumption, Cluster analysis, Routing protocol, Efficient energy use, Key distribution in wireless sensor networks, Mobile wireless sensor network, Overhead (engineering), Routing (electronic design automation), Wireless, Wireless network, Engineering, Telecommunications, Electrical engineering, Machine learning, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
29Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 9, 2024: 12, 2023: 8Per-year citation counts (last 5 years)
- References (count)
-
38Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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