Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

Gao, Yuan; Kasihmuddin, Mohd Shareduwan Mohd; Chen, Ju; Zheng, Chengfeng; Romli, Nurul Atiqah; Asyraf Mansor, Mohd.; Zamri, Nur Ezlin

doi:10.1016/j.asoc.2024.112192

Applied Soft Computing

2024

DOI: 10.1016/j.asoc.2024.112192

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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

Yuan Gao,

Mohd Shareduwan Mohd Kasihmuddin,

Ju Chen

et al.

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2024

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Optimisation of Data Flow Control Policies under Software Defined Network Architecture for Complex Network Environments

Chen,

Wan,

Qin

2024

Applied Mathematics and Nonlinear Sciences

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In recent years, with the rapid growth of Internet-related services, the traditional software-defined network architecture has gradually failed to adapt to user demands and services. This paper proposes an ant colony algorithm (ACO)-based data flow control policy optimization scheme specifically designed for software-defined networks (SDNs). It has been found that the traditional ACO algorithm is prone to overfitting during the optimization process of data flow control policies for SDN, and a pheromone updating strategy has been introduced to optimize this phenomenon. After solving this phenomenon, the optimization scheme of data flow control policy for software-defined networks based on the ACO algorithm will be formally formulated, and simulation experiments will be used to confirm the effectiveness of the optimization scheme in this paper. The results show that this paper’s algorithm has a higher priority than the control algorithm in terms of four evaluation metrics: average link throughput, link utilization, average round-trip delay, and data packet loss rate. This study enables the optimization of data flow control strategies under software-defined network architecture and also improves the utilization of network data flow to bring about a better network experience.

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Optimisation of Data Flow Control Policies under Software Defined Network Architecture for Complex Network Environments

Chen,

Wan,

Qin

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

show abstract

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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

Cited by 1 publication

References 36 publications

Optimisation of Data Flow Control Policies under Software Defined Network Architecture for Complex Network Environments

Optimisation of Data Flow Control Policies under Software Defined Network Architecture for Complex Network Environments

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