Citation: Bilal, M.; Munir, E.U.;
Alarfaj, F.K. Hybrid Clustering and
Routing Algorithm with
Threshold-Based Data Collection for
Heterogeneous Wireless Sensor
Networks. Sensors 2022, 22, 5471.
https://doi.org/10.3390/s22155471
Academic Editor: Floriano De Rango
Received: 8 June 2022
Accepted: 20 July 2022
Published: 22 July 2022
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Article
Hybrid Clustering and Routing Algorithm with
Threshold-Based Data Collection for Heterogeneous Wireless
Sensor Networks
Muhammad Bilal
1,
* , Ehsan Ullah Munir
1
and Fawaz Khaled Alarfaj
2
1
Department of Computer Science, COMSATS University Islamabad, Wah Campus,
Wah Cantt 47010, Pakistan; ehsan@ciitwah.edu.pk
2
Department of Computer Science and Information Sciences, Imam Mohammad Ibn Saud Islamic
University (IMSIU), Riyadh 11564, Saudi Arabia; fkarfaj@imamu.edu.sa
* Correspondence: mhd.bilal@ciitwah.edu.pk
Abstract:
The concept of the internet of things (IoT) motivates us to connect bulk isolated heteroge-
neous devices to automate report generation without human interaction. Energy-efficient routing
algorithms help to prolong the network lifetime of these energy-restricted smart devices that are
connected by means of wireless sensor networks (WSNs). Current vendor-level advancements enable
algorithm-level flexibility to design protocols to concurrently collect multiple application data while
enforcing the reduction of energy expenditure to gain commercial success in the industrial stage.
In this paper, we propose a hybrid clustering and routing algorithm with threshold-based data
collection for heterogeneous wireless sensor networks. In our proposed model, homogeneous and
heterogeneous nodes are deployed within specific regions. To reduce unnecessary data transmission,
threshold-based conditions are presented to prevent unnecessary transmission when minor or no
change is observed in the simulated and real-world applications. We further extend our proposed
multi-hop model to achieve more network stability in dense and larger network areas. Our proposed
model shows enhancement in terms of load balancing and end-to-end delay as compared to the other
threshold-based energy-efficient routing protocols, such as the threshold-sensitive stable election
protocol (TSEP), threshold distributed energy-efficient clustering (TDEEC), low-energy adaptive
clustering hierarchy (LEACH), and energy-efficient sensor network (TEEN).
Keywords: centralized networks; distributed networks; threshold; network heterogeneity; deletion
1. Introduction
The modern era of electronics engineering, aviation, defense, robotics, computers,
biomedical engineering, and meteorology enables researchers to design a variety of intel-
ligent wireless sensors. The set of diminutive, low-cost, energy-efficient, self-organized,
and programmable sensors are allied together to form a wireless sensor network (WSN).
These networks are generally used to accumulate valuable information without human
interaction in the domains of medical research, disaster management, engineering, tracking,
industrial operations, and surveillance in battlefields [
1
]. Recent applications of WSNs
introduced in the last decade include wave monitoring [
2
], ocean water monitoring [
3
],
cattle herding [
4
], wildlife monitoring [
5
], landslide detection [
6
], and living and residential
monitoring [7].
One of the main limitations of WSNs is the limited power available at the sensor nodes
because of their minuscule sizes, which cannot embed with massive capacity batteries,
as shown in Figure 1. In most WSN applications, nodes are randomly deployed in the target
environment, so it is impossible to collect and recharge them. Most of the prior literature on
WSNs focuses on different techniques to conserve the available energy during computations
and communications while collecting more valued data with stretched network stability.
Sensors 2022, 22, 5471. https://doi.org/10.3390/s22155471 https://www.mdpi.com/journal/sensors
