管道泄漏监测的传感器网络中数据存取算法实现

Algorithm Implementation of Information Brokerage in Pipeline Leak Monitoring Sensor Networks

针对管道泄漏和管网突发性的爆管,将自适应数据存取设计应用于管道流量泄漏监测中,数据存取是指生产者将感知数据按照策略存放在特定的位置上,消费者将查询请求按照对应策略路由到数据存放位置获得感兴趣的数据.首先依据生产者和消费者关系建模"一对一"、"多对一"、"多对多"模型来对存取代价进行分析.其次确定数据存放位置的自适应全局最优贪婪算法ODS和局部最优近似算法NDS以及最优数据传输模式.最后ODS和NDS通过自适应调整来减少数据存取能量消耗.实验表明NDS不仅节省能耗,而且在70%的情况下达到与ODS相同的效果.

Flow against pipeline leakage and the pipe network sudden burst pipe to pipeline leakage flow for the application objects, adaptive information brokerage design flow used in pipeline leak monitoring. Information brokerage in wireless sensor networks involves producers storing in storage positions a large amount of data that they have collected and consumers retrieving that information. First the data storage problem is formalized into a one-to-one model, a many-to-one model, and a many-to-many model with the goal of minimizing the total energy consumption. Second based on the above models, two algorithms are proposed to determine the storage positions based on data rates of producers, query rates of consumers, and transmission scheme of information brokerage. The optimal data storage （ ODS ） scheme, a greedy algorithm, produces the global optimal data storage positions and the near-optimal data storage （NDS） scheme, an approximate algorithm, can greatly reduce the computational overhead while achieving local optimal positions. Both ODS and NDS are able to adjust the storage positions adaptively to minimize energy consumption. Simulation results show that NDS not only provides substantial cost benefits but also performs as effective and efficient as ODS in over 70% of the tested cases.