Novel compression method reduces energy consumption and memory in wireless media sensor networks, suggesting it outperforms DCT and DWT techniques.
In recent years, Wireless Media Sensor Network (WMSN’s) deployments have rapidly increased for real time systems in various areas. Power consumption is always a critical issue which affects the overall lifetime of a wireless sensor network. WSN mainly consists of various types of sensor nodes, which are capable of sensing, computing and communicating to sink nodes wirelessly. The communication process is the main source of power consumption in the node, so a data compression technique is required which leads to a reduction in data transmitted over the wireless channels. For reducing the size of multimedia data received from media sensors, the set partitioning in a hierarchical tree (SPIHT) is always a favourable choice. But due to its huge memory requirement and complex coding, this method poses problems for resource constrained systems like a wireless media sensor network. In this paper a novel method has been introduced which is a hybrid of embedded zero tree (EZW) and set partitioning in a hierarchical tree (SPIHT). The advantages of this method is reduction of memory consumption & the processing time of the compression algorithm. The method is compared with DCT and DWT based image compression techniques for WMSN. The superiority of the algorithm over its competent algorithm has been demonstrated with the help of parameters like Peak signal to ratio (PSNR), Mean square Error (MSE), packet delivery rate, throughput, compression ratio, and energy consumption.
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Tiwari et al. (2025) studied this question.
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