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<p>Barrier coverage in Wireless Rotatable Camera Sensor Networks (WRCSNs) has attracted substantial research interest due to its potential applications in penetration detection and surveillance. Due to the energy efficiency issue, as the cameras rely on limited battery power, a major challenge is to develop an optimal scheduling strategy that maximizes the secure lifetime of WRCSNs, which is the period during which the network maintains effective barrier coverage for consistent surveillance. However, many any existing solutions struggle to achieve high accuracy or generalizability. To address these shortcomings, this paper presents a novel formulation of the maximal secure lifetime (MSL) and integral MSL (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5165_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="13" /> </InlineMediaObject> <EquationSource Format="TEX">\({\mathbb {Z}}\)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="double-struck">Z</mi> </math></EquationSource> </InlineEquation>-MSL) problems in heterogeneous WRCSNs, where sensors vary in their rotation capabilities and battery lifespans, considering active time for barrier coverage in real and integer values, respectively. The proposed SM-MSL and ESM-MSL algorithms first discretize the original problem and then transform it into a flow problem, followed by a linear programming problem, to achieve high accuracy while maintaining manageable computational costs. Additionally, we have calculated the upper bound of secure time for WRCSNs. To assess the effectiveness of the proposed algorithms, a series of tailored simulation scenarios were conducted, comparing the outcomes to prior studies. The experimental results reveal that the algorithms effectively solve the MSL and <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5165_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="13" /> </InlineMediaObject> <EquationSource Format="TEX">\({\mathbb {Z}}\)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="double-struck">Z</mi> </math></EquationSource> </InlineEquation>-MSL problems, offering superior solutions while maintaining similar computational costs.</p>

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An efficient discretization and transformation scheme for maximizing secure lifetime problem in heterogeneous wireless rotatable camera sensor networks with barrier coverage

  • 期刊论文

  • 发表日期：

    2025年6月16日

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  • Nguyen Thi My Binh,
  • Ho Viet Duc Luong,
  • Mai Dang Quan Anh,
  • Le Nam Khanh

摘要

Barrier coverage in Wireless Rotatable Camera Sensor Networks (WRCSNs) has attracted substantial research interest due to its potential applications in penetration detection and surveillance. Due to the energy efficiency issue, as the cameras rely on limited battery power, a major challenge is to develop an optimal scheduling strategy that maximizes the secure lifetime of WRCSNs, which is the period during which the network maintains effective barrier coverage for consistent surveillance. However, many any existing solutions struggle to achieve high accuracy or generalizability. To address these shortcomings, this paper presents a novel formulation of the maximal secure lifetime (MSL) and integral MSL ( \({\mathbb {Z}}\) Z -MSL) problems in heterogeneous WRCSNs, where sensors vary in their rotation capabilities and battery lifespans, considering active time for barrier coverage in real and integer values, respectively. The proposed SM-MSL and ESM-MSL algorithms first discretize the original problem and then transform it into a flow problem, followed by a linear programming problem, to achieve high accuracy while maintaining manageable computational costs. Additionally, we have calculated the upper bound of secure time for WRCSNs. To assess the effectiveness of the proposed algorithms, a series of tailored simulation scenarios were conducted, comparing the outcomes to prior studies. The experimental results reveal that the algorithms effectively solve the MSL and \({\mathbb {Z}}\) Z -MSL problems, offering superior solutions while maintaining similar computational costs.