常州工学院学报
常州工學院學報
상주공학원학보
JOURNAL OF CHANGZHOU INSTITUTE OF TECHNOLOGY
2011年
2期
1-8
,共8页
水环境监测%无线传感器网络%元胞自动机%动态簇
水環境鑑測%無線傳感器網絡%元胞自動機%動態簇
수배경감측%무선전감기망락%원포자동궤%동태족
water environment monitoring%wireless sensor network%cellular automata%dynamic cluster
面向水环境监测应用,提出了一种无线传感器网络节点动态组簇方法。该方法基于元胞自动机原理,设计了二维目标跟随元胞自动机模型。该模型以监测目标的运动特性以及相邻传感器节点状态为约束条件,使参与监测的传感器节点实现动态的组织。每个节点根据动态簇的预测信息,计算自身的休眠/活跃概率值,通过与设定的闽值比较,决定节点的休眠或活跃状态,完成退出或加入监测的动态簇。由于此方法能自适应地根据探测目标的位置和周围节点的状态重设自己的状态,因此,能够获得最佳监测效果。仿真实验表明,在探测目标不断运动的情况下,算法能很好地进行活跃节点的选择,实现能量在全局的均衡使用,大大提高了网络生存期。
麵嚮水環境鑑測應用,提齣瞭一種無線傳感器網絡節點動態組簇方法。該方法基于元胞自動機原理,設計瞭二維目標跟隨元胞自動機模型。該模型以鑑測目標的運動特性以及相鄰傳感器節點狀態為約束條件,使參與鑑測的傳感器節點實現動態的組織。每箇節點根據動態簇的預測信息,計算自身的休眠/活躍概率值,通過與設定的閩值比較,決定節點的休眠或活躍狀態,完成退齣或加入鑑測的動態簇。由于此方法能自適應地根據探測目標的位置和週圍節點的狀態重設自己的狀態,因此,能夠穫得最佳鑑測效果。倣真實驗錶明,在探測目標不斷運動的情況下,算法能很好地進行活躍節點的選擇,實現能量在全跼的均衡使用,大大提高瞭網絡生存期。
면향수배경감측응용,제출료일충무선전감기망락절점동태조족방법。해방법기우원포자동궤원리,설계료이유목표근수원포자동궤모형。해모형이감측목표적운동특성이급상린전감기절점상태위약속조건,사삼여감측적전감기절점실현동태적조직。매개절점근거동태족적예측신식,계산자신적휴면/활약개솔치,통과여설정적민치비교,결정절점적휴면혹활약상태,완성퇴출혹가입감측적동태족。유우차방법능자괄응지근거탐측목표적위치화주위절점적상태중설자기적상태,인차,능구획득최가감측효과。방진실험표명,재탐측목표불단운동적정황하,산법능흔호지진행활약절점적선택,실현능량재전국적균형사용,대대제고료망락생존기。
For the applications of water environment monitoring,this paper presents a method for dynamic grouping clusters of wireless sensor network. Such a method designs a model of two-dimensional target follow cellular automaton machine, based on cellular automata machine theory. The model makes the motion charac- teristics of target and status of the adjacent sensor device nodes as constraint conditions, so that the sensor nodes involved in monitoring can be organized dynamically. Each node calculates its own sleep/active proba- bility value,according to forecast information of dynamic cluster,as well as decides nodes in sleep or active state to complete exiting or joining a dynamic monitored cluster,through a set threshold value. Because~this method can reset their own states adaptively according to the position of detected targets and states of nodes a- round the objects,it is able to get the best monitoring results. The simulation results show that the algorithm can do well in active node selections while the detected targets keep continuous movements,so the algorithm can a- chieve balanced usage of energy in the overall situation,as well as the great improvement of network lifetime.