EE-TLT: Energy-Efficient Routing Protocol Using Two-Level Tree-based Clustering in Wireless Sensor Network

被引:1
|
作者
Tan, Nguyen Duy [1 ]
Nguyen, Van-Hau [1 ]
机构
[1] Hung Yen Univ Technol & Educ, Khoai Chau, Vietnam
关键词
Data fusion; energy balancing; energy-efficient; routing; heterogeneous wireless sensor networks; routing protocol; tree-based clustering; SCHEME;
D O I
10.23919/JCN.2023.000038
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
When designing routing protocols for wireless sensor networks, the principal challenge is to prolong the network's lifespan by effectively using the limited battery energy of the sensor nodes. To address this issue, we propose an energyefficient routing protocol employing a two-level tree-based clustering (called EE-TLT) approach to stabilize and efficiently use the sensor node's energy. In EE-TLT, the regional network is logically divided into clusters, with the number of nodes balanced in each cluster. Within each cluster, the nodes are again separated into polygons and the data is transmitted only via short links using a two-level routing tree, which is composed of one or more minimum spanning trees based on the Kruskal algorithm with a sub-cluster head (sub-CH) node serving as the root and a twolevel tree linking sub-CHs at different polygons and the base station (BS). To determine the cluster head or relay cluster head node in each polygon or sector respectively, EE-TLT considers the energy residual and distance among candidate nodes and the BS. Furthermore, EE-TLT selects the optimal data transmission stage length in each round, significantly increasing the number of data packets that the BS receives. Our experimental results demonstrate that EE-TLT not only further balances the energy consumption among sensors but also improves the ratio of data packets accepted by BS and energy efficiency compared to the LEACH-VA, PEGCP, and STDC by approximately 25%, 15%, and 10%, respectively, in both homogeneous and heterogeneous networks. The code and the simulation results of EE-TLT may be found at https://tinyurl.com/ee-tlt-wsn.
引用
收藏
页码:734 / 749
页数:16
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