Acimovic, JugoslavaCristescu, RazvanBeferull-Lozano, Baltasar2005-04-152005-04-152005-04-15200510.1109/ICASSP.2005.1416139https://infoscience.epfl.ch/handle/20.500.14299/212736WOS:000229404203209We consider large sensor networks where the cost of collecting data from the network nodes to the data gathering sink is critical.~We propose several algorithms that use limited local communication and distributed signal processing to make communication more efficient in terms of transmission cost.~We consider a model that uses distributed wavelets-based signal processing.~We first propose an algorithm that performs processing at nodes as data is forwarded to the sink.~Then, we analyze algorithms that perform network division into groups of adaptive size and for which signal processing is applied separately to each group.~We show by numerical simulations that such multiresolution approaches result in significant improvements for data gathering in terms of total communication costs.sensor networksdistributed signal processingHaar transformpiecewise defined signalsNCCR-MICSNCCR-MICS/CL1text::conference output::conference proceedings::conference paper