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Software-Defined Vehicular Ad Hoc Network (SDN-VANET), merging the Software-Defined Network (SDN) with VANET, offers many applications, from environmental monitoring to intelligent transportation systems. However, ensuring optimal performance of the networks amidst dynamic vehicular environments remains a formidable challenge. This paper proposes Particle Swarm Optimization Algorithm (PSO) and Differential Evolution Algorithm (DE) as optimal techniques in SDN-VANET, aiming to optimize TCP Window size and UDP Buffer size. After running simulations and evaluations, the results showed that these optimal algorithms effectively improved network performance components, such as increasing throughput, increasing bandwidth, reducing the number of TCP packet retransmissions, and reducing packet dropping rate (PDR).

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Performance Optimization in SDN-VANET Using Particle Swarm Optimization and Differential Evolution Algorithms

  • 会议论文

  • 发表日期：

    2025年

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  • Lam Thien Phong,
  • Bui Trung Ninh,
  • Dinh Thi Thai Mai

摘要

Software-Defined Vehicular Ad Hoc Network (SDN-VANET), merging the Software-Defined Network (SDN) with VANET, offers many applications, from environmental monitoring to intelligent transportation systems. However, ensuring optimal performance of the networks amidst dynamic vehicular environments remains a formidable challenge. This paper proposes Particle Swarm Optimization Algorithm (PSO) and Differential Evolution Algorithm (DE) as optimal techniques in SDN-VANET, aiming to optimize TCP Window size and UDP Buffer size. After running simulations and evaluations, the results showed that these optimal algorithms effectively improved network performance components, such as increasing throughput, increasing bandwidth, reducing the number of TCP packet retransmissions, and reducing packet dropping rate (PDR).