Computer Science Department, Federal University of Ouro Preto, Ouro Preto, MG, Brazil.
Sensors (Basel). 2009;9(12):9666-88. doi: 10.3390/s91209666. Epub 2009 Dec 2.
This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness.
本工作提出了一种以数据为中心的策略，以满足无线传感器网络中软实时应用的截止日期要求。该策略考虑了三个主要方面：（i）实时应用程序的设计以获得最小的截止日期；（ii）分析模型，用于估计数据缩减算法使用的理想样本大小；以及（iii）两种基于流的数据中心采样算法，以便在必要时执行数据缩减。仿真结果表明，我们的数据中心策略在满足截止日期要求的同时，不会丢失数据代表性。
