提出了一种基于规则推理的大规模无线传感器网络智能能量管理算法。该算法的核心思想是根据被监测实体以往情况以及当前状态信息,通过基于规则的推理推测出下一个时间段内实体可能发生异常或者期待事件的区域,让监测该区域的传感器节点工作,监测其他区域的节点休眠,从而提高能量效率。最后通过模拟实验对该算法进行了验证。
This paper proposed an application layer energy management algorithm (RBEM) based on intelligent reasoning, The main idea of the scheme was as follows: the parts of the entity monitored in which something abnormal or expected was possible to happen in the next time span could be predicted by analyzing the past data and the present situation of the entity, and the sensor nodes in these parts should work in the next time span while the other sensor nodes could hibernate so that energy could be saved. After that, discussed the key techniques in realizing RBEM, focusing on the issue of intelligent reasoning. Finally, compared it with other energy schemes and validated some advantages of RBEM.