Abstract
Wireless Sensor Networks (WSNs) are becoming important in today’s technology in helping monitoring our surrounding environment. However, wireless sensor nodes are powered by limited energy supply. To extend the lifetime of the device, energy consumption must be reduced. Data transmission is known to consume the largest amount of energy in a sensor node. Thus, one method to reduce the energy used is by compressing the data before transmitting it. This study analyses the performance of the Huffman and Lempel-Ziv Welch (LZW) algorithms when compressing data that are commonly used in WSN. From the experimental results, the Huffman algorithm gives a better performance when compared to the LZW algorithm for this type of data. The Huffman algorithm is able to reduce the data size by 43% on average, which is four times faster than the LZW algorithm.
Highlights
Wireless Sensor Networks (WSNs) are becoming important in today’s technology in helping monitoring our surrounding environment
This study analyses the performance of the Huffman and Lempel-Ziv Welch (LZW) algorithms when compressing data that are commonly used in WSN
The Huffman algorithm gives a better performance when compared to the LZW algorithm for this type of data
Summary
Wireless Sensor Networks (WSNs) are becoming important in today’s technology in helping monitoring our surrounding environment. Wireless sensor nodes are powered by limited energy supply. Data transmission is known to consume the largest amount of energy in a sensor node. Reduce the energy consumption is by compressing the data before transmission. Among the many components of the sensor node, the transmission module has the largest power consumption (Al-laham and El-Emary, 2007). This is because a huge amount of energy is needed to power up the wireless transmitter in order to transmit the data. One way to needed to be transmitted to other nodes reduces, reducing the power consumption due to the transmission. The higher that the data compression ratio is, the more power can be saved when transmitting the data
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