| 基于混沌并行遗传算法的多目标无线传感器网络跨层资源分配 |
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| 引用本文： | 周杰,刘元安,吴帆,张洪光,俎云霄. 基于混沌并行遗传算法的多目标无线传感器网络跨层资源分配[J]. 物理学报, 2011, 60(9): 90504-090504 |
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| 作者姓名： | 周杰 刘元安 吴帆 张洪光 俎云霄 |
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| 作者单位： | 北京邮电大学电子工程学院,北京 100876 |
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| 基金项目： | 国家高技术研究发展计划(863计划)(批准号:2008AA012211),国家自然科学基金青年科学基金项目(批准号:61003279)和国家自然科学基金面上项目(批准号:60973111)资助的课题. |
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| 摘 要： | 提出了一种基于混沌并行遗传算法的多目标无线传感器网络跨层资源分配方法,该方法运用混沌序列和并行遗传算法来动态调整传感器网络节点的探测目标及通信时隙等参数,对资源分配方式进行跨层整体优化.在多目标无线传感器网络环境下,将本文方法与传统的随机分配方法、动态规划方法、T-MAC协议及S-MAC协议等资源分配算法进行了仿真比较.仿真结果表明,本文提出的混沌并行遗传算法具有通信时延小,目标检测成功率高等优点,在降低了无线传感器网络功率消耗的同时提高了对目标检测的实时性.关键词：无线传感器网络无线资源管理Henon映射并行遗传算法
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| 关 键 词： | 无线传感器网络 无线资源管理 Henon映射 并行遗传算法 |
| 收稿时间： | 2010-11-16 |
Allocation of multi-objective cross-layer wireless sensor network resource based on chaotic parallel genetic algorithm |
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| Zhou Jie,Liu Yuan-An,Wu Fan,Zhang Hong-Guang and Zu Yun-Xiao. Allocation of multi-objective cross-layer wireless sensor network resource based on chaotic parallel genetic algorithm[J]. Acta Physica Sinica, 2011, 60(9): 90504-090504 |
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| Authors: | Zhou Jie Liu Yuan-An Wu Fan Zhang Hong-Guang Zu Yun-Xiao |
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| Affiliation: | School of Electronic Engineering, Beijng University of Posts and Telecommunications, Beijing 100876, China;School of Electronic Engineering, Beijng University of Posts and Telecommunications, Beijing 100876, China;School of Electronic Engineering, Beijng University of Posts and Telecommunications, Beijing 100876, China;School of Electronic Engineering, Beijng University of Posts and Telecommunications, Beijing 100876, China;School of Electronic Engineering, Beijng University of Posts and Telecommunications, Beijing 100876, China |
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| Abstract: | A chaotic parallel genetic algorithm for the allocation of a multi-objective cross-layer wireless sensor network resource is provided, in which chaotic sequence and parallel genetic algorithm are used to dynamically adjust target selection, communication time slots and other parameters for optimizing the global cross-layer resource allocation. Simulations are conducted to compare the chaotic parallel genetic algorithm method with random allocation algorithm, dynamic programming algorithm, T-MAC protocol and the S-MAC protocol separalely. The simulation results show that the chaotic parallel genetic algorithm has a small communication delay and high success rate of target detection, which reduces the power consumption and improves the real-time characteristic of wireless sensor network. |
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| Keywords: | wireless sensor network radio resource management Henon map parallel genetic algorithm |
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