CAJ | 학술논문

在sink移动轨迹固定的传感器网络中,由于sink点有限的通信时间和节点的随机分布,使得很难兼顾数据采集量的提高和整体能耗的降低.为了解决该问题,提出了一种最大数据量最短路径(maximum amount shortest path,简称MASP)数据采集方法.MASP对网络中成员节点与sub-sink节点之间的匹配关系进行集中式优化.采用0-1线性规划方法对MASP问题进行形式化描述,提出了一种基于二维染色体编码的遗传算法进行求解,并给出了相应的数据通信协议设计.另外,MASP可以扩展支持低密度网络和多sink点网络.基于OMNET++的仿真结果表明,MASP在能耗利用率方面要远远优于最短路径树方法(shortest path tree,简称SPT)及固定sink数据采集方法.
재sink이동궤적고정적전감기망락중,유우sink점유한적통신시간화절점적수궤분포,사득흔난겸고수거채집량적제고화정체능모적강저.위료해결해문제,제출료일충최대수거량최단로경(maximum amount shortest path,간칭MASP)수거채집방법.MASP대망락중성원절점여sub-sink절점지간적필배관계진행집중식우화.채용0-1선성규화방법대MASP문제진행형식화묘술,제출료일충기우이유염색체편마적유전산법진행구해,병급출료상응적수거통신협의설계.령외,MASP가이확전지지저밀도망락화다sink점망락.기우OMNET++적방진결과표명,MASP재능모이용솔방면요원원우우최단로경수방법(shortest path tree,간칭SPT)급고정sink수거채집방법.
In sensor networks with a path-fixed mobile sink, due to the limited communication time of the mobile sink and random deployment of the sensor nodes, it is quite difficult to increase the amount of data collected and reduce energy consumption simultaneously. To address this problem, this paper proposes a data collection scheme called maximum amount shortest path (MASP) to optimize the mapping between members and sub-sinks. MASP is formulated as an integer linear programming problem which is solved by a genetic algorithm. A communication protocol is designed to implement MASP, which is also applicable in sensor networks with low density and multiple sinks. Simulations under OMNET++ shows that MASP outperforms shortest path tree (SPT) and static sink methods in terms of energy utilization efficiency.