Data centric sensor stream reduction for real-time applications in wireless sensor networks.
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.
Computer Science Department, Federal University of Ouro Preto, Ouro Preto, MG, Brazil.
Andre Luiz Lins
AL
Aquino
Eduardo Freire
EF
Nakamura