文章基本信息

标题：A Discrete Wavelet Transform (DWT)-Based Energy-Efficient Selective Retransmission Mechanism for Wireless Image Sensor Networks
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作者：Daniel G. Costa ; Luiz Affonso Guedes
期刊名称：Journal of Sensor and Actuator Networks
电子版ISSN：2224-2708
出版年度：2012
卷号：1
期号：1
页码：3-35
DOI：10.3390/jsan1010003
语种：English
出版社：MDPI Publishing
摘要：Source nodes in wireless image sensor networks transmit much more information than traditional scalar sensor networks, thereby demanding more energy of intermediate relaying nodes and putting energy efficiency as a key design issue. Intermediate nodes are usually interconnected by error-prone links where bit-errors are common, potentially degrading the application monitoring quality. When reliability is assured by retransmission mechanisms, higher packet error rates do not affect the application quality but result in additional energy consumption due to packet retransmission, even though many monitoring applications can tolerate some loss in the quality of the received image. DWT coding can decompose an image in data subbands, each one with different relevancies for the reconstruction of the original image at the receiver side. We propose an energy-efficient selective hop-by-hop retransmission mechanism where the reliability level of each packet is a function of the relevance of the payload data, according to the resulting subbands and the number of times a 2D DWT is applied over the images captured by the sensors’ cameras. In so doing, some lost packets are not retransmitted, saving energy of intermediate nodes with low impact to the quality of the reconstructed images. In order to estimate the benefits of this tradeoff between energy consumption and image quality, we designed a comprehensive energy consumption model and applied it in extensive mathematic simulations, providing substantial information about the mean performance of the proposed approach when compared with a fully-reliable transmission mechanism.
关键词：wireless image sensor networks; DWT; hop-by-hop retransmission; energy-efficiency; wireless sensor networks