Publication: Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks
Loading...
Date
2024-03
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Islam Malaysia
Abstract
Wireless Sensor Networks (WSNs) are becoming increasingly ubiquitous in a wide range
of applications, such as agriculture monitoring, industrial automation, and healthcare.
However, their operation in resource-constrained environments presents unique challenges,
including data loss, node failure, and limited network lifetime, which can significantly
impact their performance and reliability. This thesis investigates the challenges and existing
solutions related to data loss, node failure, and network lifetime aspects of WSNs. This
research proposes a hybrid Tri-Head Fuzzy C Mean Clustering Multipath Routing Protocol
(THFCMRP) that helps make WSNs more reliable, consistent, and long-lasting by
addressing these critical issues. The proposed THFCMRP approach is designed by a trihead
fuzzy c means clustering integrated with a multi-path routing protocol approach.
Initially, groups of sensor nodes are clustered using a fuzzy c means clustering approach.
Then, three Cluster Heads (CHs) such as Aggregation Cluster Head (ACH), Transmitting
Cluster Head (TCH), and Backup Cluster Head (BCH), are selected. These CHs include
various roles and functions. The responsibility of ACH is to aggregate data from cluster
members and transmit it to TCH. The information is collected by TCH and then transmitted
to BS. However, BCH plays a crucial role in ensuring network consistency and data
availability. The BCH helps reduce the data loss caused by TCH and Base Station (BS)
failures. The BCH offers data redundancy, improves energy efficiency, and enhances
network consistency and data availability by taking over for failing aggregate and
transmitting cluster heads. A multi-path routing protocol is used to generate an optimal path
from the TCH to the BS for data transmission. TCH uses an optimal path that consumes
less energy for data transfer, thus diminishing data loss and extending the network's
life. Thus, the proposed approach optimizes network performance by minimizing data loss,
maintaining network performance upon any node failure incident, and extending the
network's lifetime. Data Backup, Average Correct Data Packet Transferred, Data Loss, End
to End Delay, Normalized Overheads, Packet Delivery Ratio, Throughput, Routing
Overhead, Number of Alive Nodes, Packet Drop Ratio, and Residual Energy metrics are
evaluated to assess the efficiency of the proposed approach. The packet delivery rate of the
proposed algorithm is 98%, indicating that it causes lower node failure and data loss. The
data loss ratio is 0.2%, meaning most packets are successfully delivered to their destination.
Compared to the existing algorithms H2B2H, FTCM, HFGWO, DHSCA, and EACNF, the
proposed technique achieves 83% energy efficiency. Our results demonstrated that the
proposed algorithm offers better network consistency and data availability within a WSN.
Description
Matric: 4171001 (FST)-Restricted until Mac 2027
Keywords
Clustering, Energy consumption, Wireless Sensor Networks (WSNs), Fuzzy systems, Fuzzy c means, Internet of things (IoT), Scalability, Cluster Heads (CHs), Aggregation Cluster Head (ACH), Transmitting Cluster Head (TCH), Backup Cluster Head (BCH)
Citation
Mujahid Tabassum. (2024). Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks [Doctoral dissertation, Universiti Sains Islam Malaysia]. USIM Research Repository.