| 基于粒子群优化的主动队列管理方法 |
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| 引用本文： | 王军祥,林柏钢.基于粒子群优化的主动队列管理方法[J].计算机应用,2013,33(2):390-396. |
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| 作者姓名： | 王军祥 林柏钢 |
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| 作者单位： | 1. 福建船政交通职业学院 信息工程系，福州 3500072. 网络系统信息安全福建省高校重点实验室(福州大学)，福州 350108 |
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| 基金项目： | 福建省信息安全重点项目 |
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| 摘 要： | 针对网络拥塞现象，基于粒子群优化(PSO)提出了一种新的主动队列管理算法RQQM。该算法首先通过粒子群优化和变异算子来计算当前队列长度，并且基于到达速率和当前队列长度给出了丢包策略和丢包概率。最后，以实际数据将RQQM算法与基于速率的早期检测公平队列管理(RFED)算法和自适应主动队列管理(ABLUE)算法进行仿真实验，
发现丢包率受利用率和缓冲区影响较大;同时实验结果表明RQQM算法的公平性远远优于其他两种算法，其平均丢包率降低至12.21%。
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| 关 键 词： | 主动队列管理 丢包概率 粒子群优化 队列长度 到达速率 |
| 收稿时间： | 2012-08-29 |
| 修稿时间： | 2012-10-19 |
Active queue management algorithm based on particle swarm optimization |
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| WANG Junxiang
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LIN Bogang.Active queue management algorithm based on particle swarm optimization[J].journal of Computer Applications,2013,33(2):390-396. |
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| Authors: | WANG Junxiang LIN Bogang |
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| Affiliation: | 1. Department of Information Technology and Engineering, Fujian Chuanzheng Communications College, Fuzhou Fujian 350007, China2. Key Laboratory of Information Security of Network Systems (Fuzhou University), Fuzhou Fujian 350108, China |
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| Abstract: | In order to mitigate the network congestion, a novel active queue management algorithm RQQM (Rate and Queue-based Queue Management algorithm) is proposed by particle swarm optimization. In this algorithm, actual queue length is deducted with particle swarm optimization and variation factor, and the dropping strategy and dropping rate are presented based on arrival rate and actual queue length. Then, a simulation with actual data was conducted to study of the algorithm performance between RQQM and RFQM (Rate-based Fair Queue Management algorithm), as well as ABLUE (Adaptive BLUE algorithm). The result shows that it is better adaptability for RQQM. |
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| Keywords: | Active Queue Management (AQM) dropping rate Particle Swarm Optimization (PSO) queue length arrival rate |
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