Blackboard Mechanism Based Ant Colony Theory for Dynamic Deployment of Mobile Sensor Networks
Blackboard Mechanism Based Ant Colony Theory for Dynamic Deployment of Mobile Sensor Networks
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DOI：
10.1016/s1672-6529(08)60025-6
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发表时间：
2008-09-01
影响因子：
4
通讯作者：
Li, Ke-jie
中科院分区：
文献类型：
--
作者：
Qi, Guang-ping;Song, Ping;Li, Ke-jie
针对移动传感器网络的自治性和动态部署问题，提出了一种基于黑板机制的仿生群体智能算法--蚁群算法。系统中引入黑板机制来生成信息素和完成算法。每一个节点都可以看作是一只蚂蚁，它在自己的记忆中建立一个信息区，用来与其他节点进行通信，并留下信息素，这些信息素是自然界中蚂蚁自己产生的。然后利用蚁群算法对移动的无线传感器网络的路径规划和部署进行优化。我们在一个动态的和不可配置的环境中测试的算法。实验结果表明，该算法平均降低功耗13%，使移动的WSN路径规划和部署效率平均提高15%。
A novel bionic swarm intelligence algorithm, called ant colony algorithm based on a blackboard mechanism, is proposed to solve the autonomy and dynamic deployment of mobiles sensor networks effectively. A blackboard mechanism is introduced into the system for making pheromone and completing the algorithm. Every node, which can be looked as an ant, makes one information zone in its memory for communicating with other nodes and leaves pheromone, which is created by ant itself in nature. Then ant colony theory is used to find the optimization scheme for path planning and deployment of mobile Wireless Sensor Network (WSN). We test the algorithm in a dynamic and unconfigurable environment. The results indicate that the algorithm can reduce the power consumption by 13% averagely, enhance the efficiency of path planning and deployment of mobile WSN by 15% averagely.