Scholarlink

<p>The rapid expansion of Internet of Things (IoT) applications has increased the demand for high computing power, often beyond the capabilities of mobile devices limited by processing speed and battery life. Vehicular fog computing offers a solution by utilizing parked vehicles as computational nodes, bringing resources closer to users. The main objective of this study is to explore the use of electric vehicles as computational nodes in a fog computing architecture, allowing mobile users to offload tasks to these idle vehicles. To manage these distributed resources efficiently, a Software-Defined Networking (SDN) controller is integrated to monitor vehicle parameters such as power, energy, and parking duration, and to dynamically allocate computation requests. Simulation experiments conducted in MATLAB Simulink demonstrate that the proposed system reduces computation time by up to 45%, decreases energy consumption by nearly 30%, and improves fog resource utilization by more than 40% compared with local execution. The results also reveal how the weighting factors (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\alpha\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\beta\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\gamma\)</EquationSource> </InlineEquation>) influence the decision-making process and help maintain a balance between performance, energy efficiency, and stability. Overall, integrating SDN control with parked electric vehicles enables faster, energy-aware, and more reliable computing services for mobile IoT applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The SDN for fog computing in VANETs

  • 期刊论文

  • 发表日期：

    2026年7月14日

查看全文
  • Ali Kies,
  • Amal Boumedjout,
  • Zoulikha Mekkakia Maaza,
  • Farah Hachem

摘要

The rapid expansion of Internet of Things (IoT) applications has increased the demand for high computing power, often beyond the capabilities of mobile devices limited by processing speed and battery life. Vehicular fog computing offers a solution by utilizing parked vehicles as computational nodes, bringing resources closer to users. The main objective of this study is to explore the use of electric vehicles as computational nodes in a fog computing architecture, allowing mobile users to offload tasks to these idle vehicles. To manage these distributed resources efficiently, a Software-Defined Networking (SDN) controller is integrated to monitor vehicle parameters such as power, energy, and parking duration, and to dynamically allocate computation requests. Simulation experiments conducted in MATLAB Simulink demonstrate that the proposed system reduces computation time by up to 45%, decreases energy consumption by nearly 30%, and improves fog resource utilization by more than 40% compared with local execution. The results also reveal how the weighting factors ( \(\alpha\) , \(\beta\) , \(\gamma\) ) influence the decision-making process and help maintain a balance between performance, energy efficiency, and stability. Overall, integrating SDN control with parked electric vehicles enables faster, energy-aware, and more reliable computing services for mobile IoT applications.