Distributed Multi-hop Clustering Approach with Low Energy Consumption in WSN

The purpose of sensing the environment and geographical positions,
device monitoring, and information gathering are accomplished using Wireless
Sensor Network (WSN), which is a non-dependent device consisting of a distinct
collection of Sensor Node (SN). Thus, a clustering based on Energy Efficient
(EE), one of the most crucial processes performed in WSN with distinct environ
ments, is utilized. In order to efficiently manage energy allocation during sensing
and communication, the present research on managing energy efficiency is per
formed on the basis of distributed algorithm. Multiples of EE methods were
incapable of supporting EE routing with MIN-EC in WSN in spite of the focus
of EE methods on energy harvesting and minimum Energy Consumption (EC).
The three stages of performance are proposed in this research work. At the outset,
during routing and Route Searching Time (RST) with fluctuating node density
and PKTs, EC is reduced by the Hybrid Energy-based Multi-User Routing
(HEMUR) model proposed in this work. Energy efficiency and an ideal route
for various SNs with distinct PKTs in WSN are obtained by this model. By utiliz
ing the Approximation Algorithm (AA), the Bregman Tensor Approximation
Clustering (BTAC) is applied to improve the Route Path Selection (RPS) effi
ciency for Data Packet Transmission (DPT) at the Sink Node (SkN). The
enhanced Network Throughput Rate (NTR) and low DPT Delay are provided
by BTAC. To MAX the Clustering Efficiency (CE) and minimize the EC, the
Energy Effective Distributed Multi-hop Clustering (GISEDC) method based on
Generalized Iterative Scaling is implemented. The Multi-User Routing (MUR)
is used by the HEMUR model to enhance the EC by 20% during routing. When
compared with other advanced techniques, the Average Energy Per Packet
(AEPP) is enhanced by 39% with the application of proportional fairness with
Boltzmann Distribution (BD). The Gaussian Fast Linear Combinations (GFLC)
with AA are applied by BTAC method with an enhanced Communication Over
head (COH) for an increase in performance by 19% and minimize the DPT delay
This work is licensed under a Creative Commons Attribution 4.0 International License, which
permits unrestricted use, distribution, and reproduction in any medium, provided the original
work is properly cited.
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CSSE, 2023, vol.45, no.1
by 23%. When compared with the rest of the advanced techniques, CE is
enhanced by 8% and EC by 27% with the application of GISEDC method.
Keywords: Sensor node; clustering; routing; energy consumption; multi-path
routing