Performance comparison of data compression algorithms for environmental monitoring wireless sensor networks

Jonathan Gana Kolo*, Li Minn Ang, Kah Phooi Seng, S. R.S. Prabaharan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Wireless sensor networks (WSNs) have serious resource limitations ranging from finite power supply, limited bandwidth for communication, limited processing speed, to limited memory and storage space. Data compression can help reduce memory and storage space requirements on sensor node. In WSNs, radio communication is the major consumer of energy. Therefore, applying data compression before transmission will significantly and directly help in reducing total power consumption of a sensor node thereby extending the network lifetime. In this article, we propose a simple lossless data compression algorithm designed specifically to be used by environmental monitoring sensor nodes for the compression of environmental data which are characterise by significant fluctuations in entropy. To verify the effectiveness of our proposed algorithm, we compare its compression performance with two existing WSNs compression algorithms using real-world environmental datasets. We show that our algorithm outperforms the other two algorithms when the entropy of the dataset is large.

Original languageEnglish
Pages (from-to)65-75
Number of pages11
JournalInternational Journal of Computer Applications in Technology
Issue number1
Publication statusPublished - 2013
Externally publishedYes


  • Data compression
  • Energy efficient
  • Huffman coding
  • WSNs
  • Wireless sensor networks


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