Dynamic Itinerary Planning for Mobile Agents with a Content-Specific Approach in Wireless Sensor Networks
Dynamic Itinerary Planning for Mobile Agents with a Content-Specific Approach in Wireless Sensor Networks
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DOI：
10.1109/vetecf.2010.5594122
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发表时间：
2010-10
期刊：
影响因子：
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通讯作者：
K. Ota;M. Dong;Junbo Wang;Song Guo;Zixue Cheng;M. Guo
中科院分区：
文献类型：
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作者：
K. Ota;M. Dong;Junbo Wang;Song Guo;Zixue Cheng;M. Guo
利用移动agent （mobile agent, MAs）研究传感器网络中的数据融合，它能够节省传感器节点的能量，并根据各种应用的要求执行高级计算功能。在面向应用的数据融合的发展中，MAs的研究仍然不成熟，而这在最近部署的用于环境和灾害监测的无线传感器网络（WSNs）中是非常需要的。在本文中，我们提出了一个动态行程规划的MAs (DIPMA)，以应用为导向的方法从传感器网络中收集数据。特别是，DIPMA算法被应用于霜冻预测的数据收集，这是使用下一代传感器网络在农业中的实际应用。通过仿真对DIPMA的性能进行了评价，实验结果表明，该方法在保持良好预测精度的同时，显著缩短了DIPMA的总执行时间。
We study data fusion in sensor networks using mobile agents (MAs),which are capable of saving energy of sensor nodes and performing advanced computation functions based on the requests of various applications. Research on MAs still remains unfledged in development of application-oriented data fusion, which is highly desired in wireless sensor networks (WSNs) deployed in recent days for environmental and disaster monitoring. In this paper, we propose a dynamic itinerary planning for MAs (DIPMA) to collect data from sensor networks with an application-oriented approach. In particular, the DIPMA algorithm is applied to the data collection for frost prediction which is a real-world application in agriculture using next- generation sensor networks. The performance of the DIPMA is evaluated by simulations and the experimental results show that the total execution time of MA can be reduced significantly with our approach while sound prediction accuracy is maintained.