FELZMACS: A Novel Data Compression Model in Wireless Sensor Networks for Fast Data Transfer


  • Seelamanthula Sreenivasu Research Scholar, Department of Computer Sciences & Systems Engineering, A.U.College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India.
  • James Stephen Meka Dr. B. R. Ambedkar Chair Professor, Dean, A.U. TDR-HUB,Andhra University, Visakhapatnam, Andhra Pradesh, India.


Data compression in wireless sensor networks, Hybrid approaches in data compression, fast transmission in wireless sensor networks, FELACS Compression, LZMA compression


Recent research on Wireless Sensor Networks has been multi-dimensional and exhaustive. Data compression is one area being focused, due to the reason that the data originated from the sensors and transmitted to the base station through intermediate entities require fast transmission. The data compression during the transmission effectively results in faster communication, node lifetime improvement as well slight protection of the data. The research on data compression encompasses various techniques proposed that include discrete cosine transform, run length encoding, embedded zero tree wavelet coding, and so on. It is well known that incorporating data compression into WSN further enhances energy efficiency. In this paper, a hybrid approach “Fast and Efficient Lempel Ziv Markov-Chain Adaptable Compression Scheme (FELZMACS)” involving two techniques namely Fast and efficient lossless adaptive compression scheme (FELACS) and Lempel Ziv Markov chain Algorithm (LZMA) methods are used for compressing the data each at a different level. The former approach is used to compress the data between the node and cluster head while the latter approach is used for data compression between the cluster head and the base station. The performance of this hybrid approach in terms of energy efficiency and delay is remarkable.


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How to Cite

Sreenivasu, S. ., & Meka, J. S. . (2023). FELZMACS: A Novel Data Compression Model in Wireless Sensor Networks for Fast Data Transfer. International Journal of Intelligent Systems and Applications in Engineering, 12(2), 214–224. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4244



Research Article