基于LA-ABC的校园楼宇传感器网络的定位方法分析研究

Research on location method of sensor network of campus building based on LA-ABC

针对校园楼宇温度控制系统中,如何以最优路径将终端传感器温度信息传输到控制端这个问题。通过分析要达到最优路径的信息传输,重要的是要解决每个节点传感器定位的问题。为此提出了一种改进的人工蜂群算法用于提高节点传感器的定位精度(LA-ABC:Location ApproachArtificial Bee Colony Algorithm),主要是利用混沌反向学习策略初始化种群,设计自适应的动态方法调整蜜源更新公式。通过测试,利用该方法有效的提高了温控系统中节点传感器的定位精度。在相同条件下,与传统的DV-Hop定位算法比较表明,LA-ABC的平均定位误差明显小于DVHop。

How to transmit the terminal sensor temperature information to the control terminal through optimal path is a problem concerning temperature control system of the campus building. The focus is to solve the problem of sensor positioning for each node by getting the optimal path through analyzing the information transmission. As a result,an improved artificial bee colony algorithm is proposed to improve the positioning accuracy of node sensor in this paper（LA-ABC： Location Approach-Artificial Bee Colony Algorithm）. This approach can initialize the population through chaos reverse learning strategy and design the adaptive dynamic method to adjust the formula of nectar regeneration. Through the test,this approach can effectively improve the positioning accuracy of the node sensor in the temperature control system. Under the same conditions,compared with the traditional localization algorithm of DVHop,the average positioning error of LA-ABC is significantly less than that of DV-Hop.