<p>The random and dense deployment of wireless sensor networks (WSNs) creates overlapping regions and correlated nodes which sense and report redundant data to the base station (BS), resulting in a significant energy consumption and shorter network lifetime. Reducing redundant data transmissions in the network, whilst maintaining sufficient data transfer to the BS, low energy consumption, and consistent network performance is a challenging task. This paper proposes a clustering-based sleep scheduling protocol (RMIS) that aims to reduce redundant transmissions and improve network energy consumption. To achieve this, it uses the set of independent vertices and a proposed <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11276_2025_3971_Article_IEq1.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="10" /> </InlineMediaObject> <EquationSource Format="TEX">$\epsilon $</EquationSource> <EquationSource Format="MATHML"><math> <mi>ϵ</mi> </math></EquationSource> </InlineEquation>-greedy triggering algorithm to rotate between sleep and awake states. The correlated nodes in a cluster are first identified according to their distance and sensing range, then used to generate a representative graph for each cluster according to the relationship between the nodes. To reduce data transmissions, RMIS considers the nodes in each cluster’s independent vertex set as awake nodes. The node states are determined according to an <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11276_2025_3971_Article_IEq1.gif" Format="GIF" Height="10" Rendition="HTML" Resolution="72" Type="Linedraw" Width="10" /> </InlineMediaObject> <EquationSource Format="TEX">$\epsilon $</EquationSource> <EquationSource Format="MATHML"><math> <mi>ϵ</mi> </math></EquationSource> </InlineEquation>-greedy triggering algorithm, which allows new cluster configurations to be explored and less energy-consuming ones to be exploited. RMIS also performs clustering using the Chinese Whisper algorithm, based on the distance and transmission range of the nodes, which helps create compact and separate clusters. The simulation results confirm the superiority of the proposed protocol over the comparative approaches, notably in terms of network lifetime, stability period, energy consumption, and number of alive nodes.</p>

RMIS: an independent vertex set based sleep scheduling protocol for network lifetime maximization in WSNs

期刊论文
发表日期：

2025年5月25日

查看全文

Nour El Houda Bourebia,
Soumia Bourebia

摘要

The random and dense deployment of wireless sensor networks (WSNs) creates overlapping regions and correlated nodes which sense and report redundant data to the base station (BS), resulting in a significant energy consumption and shorter network lifetime. Reducing redundant data transmissions in the network, whilst maintaining sufficient data transfer to the BS, low energy consumption, and consistent network performance is a challenging task. This paper proposes a clustering-based sleep scheduling protocol (RMIS) that aims to reduce redundant transmissions and improve network energy consumption. To achieve this, it uses the set of independent vertices and a proposed $\epsilon $ $ϵ$ -greedy triggering algorithm to rotate between sleep and awake states. The correlated nodes in a cluster are first identified according to their distance and sensing range, then used to generate a representative graph for each cluster according to the relationship between the nodes. To reduce data transmissions, RMIS considers the nodes in each cluster’s independent vertex set as awake nodes. The node states are determined according to an $\epsilon $ $ϵ$ -greedy triggering algorithm, which allows new cluster configurations to be explored and less energy-consuming ones to be exploited. RMIS also performs clustering using the Chinese Whisper algorithm, based on the distance and transmission range of the nodes, which helps create compact and separate clusters. The simulation results confirm the superiority of the proposed protocol over the comparative approaches, notably in terms of network lifetime, stability period, energy consumption, and number of alive nodes.