Research Article
Energy and Distance Aware Clustering-Based Routing for Low-Power IoT-Enabled Wireless Sensor Networks
@INPROCEEDINGS{10.1007/978-3-031-67357-3_10, author={Viet-Thanh Le and Nguyen-Son Vo and Minh-Phung Bui and Lan P. Le}, title={Energy and Distance Aware Clustering-Based Routing for Low-Power IoT-Enabled Wireless Sensor Networks}, proceedings={Industrial Networks and Intelligent Systems. 10th EAI International Conference, INISCOM 2024, Da Nang, Vietnam, February 20--21, 2024, Proceedings}, proceedings_a={INISCOM}, year={2024}, month={7}, keywords={Ant Colony based Routing Clustering-based Routing Energy-aware Routing Fuzzy Logic Model Internet of Things K-means Clustering Wireless Sensor Networks}, doi={10.1007/978-3-031-67357-3_10} }- Viet-Thanh Le
Nguyen-Son Vo
Minh-Phung Bui
Lan P. Le
Year: 2024
Energy and Distance Aware Clustering-Based Routing for Low-Power IoT-Enabled Wireless Sensor Networks
INISCOM
Springer
DOI: 10.1007/978-3-031-67357-3_10
Abstract
The ever-increasing demand for Internet of Things (IoT) applications leads to the deployment of a massive amount of devices in wireless sensor networks (WSNs). The IoT-enabled WSNs suffer from the problems of often non-rechargeable, non-replaceable, and limited battery sources of sensing devices, namely low-power IoT-enabled WSNs. This paper addresses these problems by proposing an energy and distance aware clustering-based routing (EDCR) method. Particularly, in the clustering phase, a fuzzy-assisted K-means clustering (FKMC) technique is applied to ensure that the distribution of sensors in all clusters is similar and the cluster heads have enough energy resources to communicate with the base station (BS). In the routing phase, a fuzzy-assisted ant colony based routing (FACR) algorithm is deployed to find the optimal paths from the source sensors to the BS by identifying the intermediate sensors based on the residual energy for communications, the distance from the current sensor to the following one, and the distance from the follower to the BS. As a result, the proposed EDCR method can balance the workload of sensors among clusters by FKMC to significantly enhance the energy efficiency for low-power IoT-enabled WSNs by FACR compared to other conventional schemes.
