摘要
当无线传感监测网中事件分布不均匀时,使用以数据为中心的存储算法会出现热点现象。为此,引入存储阈值与时间优先级,选择存储节点时考虑节点剩余存储空间,提出一种新的蛇形时隙数据存储算法。根据事件优先级确定事件存储位置到查询节点网格的距离,减少数据存储和查询过程中的能量消耗。通过定义节点存储阈值确定是否进入下一轮时隙分配。当网格内节点都达到存储阈值时,将数据存储于其他同一优先级的邻居网格内。当同一优先级的所有网格内节点都达到某一存储阈值时,重新分配工作时隙,以解决节点能量分布不均的问题。仿真结果表明,该算法在节点剩余能量和网络生命周期方面性能均优于基于事件优先级的蛇形时隙存储算法。
When events distribute nonuniformly in the wireless sensor monitoring network, hot spots will appear in data- centric storage algorithms. Aiming at this problem,this paper introduces storage thresholds and event priorities,considers nodes＇ remaining memory when selecting storage nodes, and proposes a new snake-like slot time data storage algorithm. It determines the distance from event storage location to query node grid according to the event priority,to reduce node＇ s energy consumption in process of data storage and query. Defining a node storage threshold,nodes reaching the threshold are no longer involved in the next round of time slot allocation. When all nodes in a grid reach the storage threshold, it stores data into neighbor grids with the same priority level. When all nodes in all grids of the same priority reach one storage threshold,it reallocates work slot, which effectively reduces the nonuniform distribution. Simulation results show that the proposed algorithm has better performance than the Snake-like Slot Time Power-saving Data Stroage Algorithm based on Event Priority（P-SLPS） in residual energy of nodes and the network life cycle.
出处
《计算机工程》
CAS
CSCD
北大核心
2016年第12期32-38,共7页
Computer Engineering
基金
国家自然科学基金(61372011)
