Querying Uncertain Minimum in Wireless Sensor Networks
In this paper, we introduce two types of probabilistic aggregation queries, namely, Probabilistic Minimum Value Queries (PMVQ)s and Probabilistic Minimum Node Queries (PMNQ)s. A PMVQ determines possible minimum values among all imprecise sensed data, while a PMNQ identifies sensor nodes that possibly provide minimum values. However, centralized approaches incur a lot of energy from battery-powered sensor nodes and well-studied in-network aggregation techniques that presume precise sensed data are not practical to inherently imprecise sensed data. Thus, to answer PMVQs and PMNQs energy-efficiently, we devised suites of in-network algorithms. For PMVQs, our in-network minimum value screening algorithm (MVS) filters candidate minimum values; and our in-network minimum value aggregation algorithm (MVA) conducts in-network probability calculation. PMNQs requires possible minimum values to be determined a prior, inevitably consuming more energy to evaluate than PMVQs. Accordingly, our one-phase and two-phase in-network algorithms are devised. We also extend the algorithms to answer PMNQ variants. We evaluate all our proposed approaches through cost analysis and simulations.
wireless sensor network uncertain data data aggregation minimum queries algorithms and performance