改进的低时延全回波Q路由算法

doi:10.3969/j.issn.1001-506X.2020.04.27

系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (4): 940-947.doi: 10.3969/j.issn.1001-506X.2020.04.27

改进的低时延全回波Q路由算法

黄庆东(), 袁润芝(), 郭民鹏(), 石斌宇(), 曹艺苑()

西安邮电大学通信与信息工程学院, 陕西西安 710121

收稿日期:2019-08-01 出版日期:2020-03-28 发布日期:2020-03-28
作者简介:黄庆东(1976-),男,副教授,博士,主要研究方向为自适应信号处理、机器学习。E-mail:huangqingdong@xupt.edu.cn|袁润芝(1995-),女,硕士研究生,主要研究方向为无线传感器网络、机器学习。E-mail:939683341@qq.com|郭民鹏(1995-),男,硕士研究生,主要研究方向为无线传感器网络、机器学习。E-mail:83782978@qq.com|石斌宇(1993-),男,硕士研究生,主要研究方向为无线传感器网络、机器学习。E-mail:243660601@qq.com|曹艺苑(1997-),女,硕士研究生,主要研究方向为无线传感器网络、机器学习。E-mail:331812722@qq.com
基金资助:
国家科技重大专项(2017ZX03001012-005);陕西省教育厅科学研究计划(17JK0693);陕西省重点科技创新团队计划(2017KCT-30-02)

Advanced low delay Q-routing algorithm based on full echoes

Qingdong HUANG(), Runzhi YUAN(), Minpeng GUO(), Binyu SHI(), Yiyuan CAO()

School of Communication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China

Received:2019-08-01 Online:2020-03-28 Published:2020-03-28
Supported by:
国家科技重大专项(2017ZX03001012-005);陕西省教育厅科学研究计划(17JK0693);陕西省重点科技创新团队计划(2017KCT-30-02)

摘要/Abstract

摘要：

针对传统路由算法不能适应拓扑环境及网络负载变化导致的拥塞问题,提出了一种改进的低时延全回波Q路由算法。改进算法对于原有算法附加学习率因子进行替换,使用调节范围更大、适应性更好、算法性能更稳健的双曲正割算子;改进算法根据不同网络情况自适应地调节学习率,进而提供合理的路由决策。仿真结果表明,该算法可以适应于静、动态拓扑环境,与已有的路由算法相比,改进算法能有效地减少高、低负载时数据的平均递交时间,降低路由间的振荡,提高数据包的投递率,且体现更好的稳健性。

关键词: 自组织网络, Q路由, 全回波, 自适应

Abstract:

Aiming at the congestion problem caused by traditional routing algorithms which cannot adapt to changes in topological environment and network load, an improved low delay Q-routing algorithm based on full echoes is proposed. The additional learning rate factor, that of the original algorithm, is replaced by the hyperbolic secant operator, which has a larger adjustment range, better adaptability and more robust performance. The learning rate in the improved algorithm could be adjusted adaptively according to different network conditions, which provides reasonable routing decision. The simulation results show that the algorithm can be suitable for static and dynamic topological environment. Compared with the original algorithm, the improved algorithm can effectively reduce the average delivery time of data under high and low loads, cut down on the oscillations between routes, improve the delivery rate of data packets, and reflect better robustness in the medium load.

Key words: self-organizing network, Q-routing, full echo, self-adaption

中图分类号:

TN911

黄庆东, 袁润芝, 郭民鹏, 石斌宇, 曹艺苑. 改进的低时延全回波Q路由算法[J]. 系统工程与电子技术, 2020, 42(4): 940-947.

Qingdong HUANG, Runzhi YUAN, Minpeng GUO, Binyu SHI, Yiyuan CAO. Advanced low delay Q-routing algorithm based on full echoes[J]. Systems Engineering and Electronics, 2020, 42(4): 940-947.

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参考文献 17

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仿真参数	值
仿真模型	不规则固定拓扑
仿真时间	10 000单位时间
网络负载	服从指数为λ的泊松分布
学习率η	0.9
包的记忆长度L	1
节点队列最大缓存包数	50
k	0.6
k₂	0.3

仿真参数	值
仿真模型	RWM移动模型
仿真区域面积	1 500 m×1 500 m
仿真时间	10 000单位时间
移动模型节点数量	100
节点移动最大速度	10 m/单位时间
传输范围/m	250
k	0.6
k₂	3

算法	各节点对投递率/%					总投递率/%
算法	0~17	1~23	2~29	7~10	8~4	总投递率/%
AQFE-M算法	84.70	84.67	85.31	85.88	87.90	85.33
改进算法	85.52	85.76	87.24	86.75	89.08	86.77

算法	各节点对投递率/%					总投递率/%
算法	0~17	1~23	2~29	7~10	8~4	总投递率/%
AQFE-M算法	61.50	60.47	65.20	60.88	62.04	61.98
改进算法	64.87	60.89	67.67	62.38	63.12	63.81

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改进的低时延全回波Q路由算法

Advanced low delay Q-routing algorithm based on full echoes

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