基于多级模糊评判的高效数据聚集算法

An Efficient Algorithm of Data Aggregation Based on Multi-level Fuzzy Comprehensive Evaluation

基于多级模糊综合评判,提出一种既可节省传感节点能量又能提高数据聚集度和减少数据传输延迟的高效的数据聚集算法。先由一级模糊综合评判获得路由信息,然后根据路由表中相邻传感节点转发的数据包个数,利用二级模糊综合评判重新选择下一跳传感节点,通过增加原有路径间交叠的方式来高效的提高数据聚集度;然后为了均衡能耗和减少传输延迟提出一种新的聚集定时机制。仿真结果表明,该算法能延长网络生命周期,提高数据包交付率,降低平均传输延迟及提升数据聚集度。

Based on multi-level fuzzy comprehensive evaluation,an efficient data aggregation algorithm is proposed which is able to save energy of sensor nodes,improve data aggregation performance and reduce data transmission delay.Onelevel fuzzy comprehensive assessment is used to obtain routing information.Then secondary fuzzy comprehensive evaluation is used to reselect the next-hop sensor node,according to the number of packets forward in a period through the original optimal routing,as well as improving data aggregation performance by increasing the overlap of the original paths.Moreover,the data aggregation timing mechanism can effectively balance the average energy consumption of each sensor node,and reduce average data delay.Simulation result shows that this algorithm can prolong the network lifetime,enhance the packet delivery ratio greatly,reduce data transmission delay and improve data aggregation performance.