Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Implementation of Modified Huffman Coding in Wireless Sensor Networks

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
M. Malleswari, B. Ananda Krishna, N. Madhuri, M. Kalpana Chowdary
10.5120/ijca2017915564

M Malleswari, Ananda B Krishna, N Madhuri and Kalpana M Chowdary. Implementation of Modified Huffman Coding in Wireless Sensor Networks. International Journal of Computer Applications 177(1):14-17, November 2017. BibTeX

@article{10.5120/ijca2017915564,
	author = {M. Malleswari and B. Ananda Krishna and N. Madhuri and M. Kalpana Chowdary},
	title = {Implementation of Modified Huffman Coding in Wireless Sensor Networks},
	journal = {International Journal of Computer Applications},
	issue_date = {November 2017},
	volume = {177},
	number = {1},
	month = {Nov},
	year = {2017},
	issn = {0975-8887},
	pages = {14-17},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume177/number1/28590-2017915564},
	doi = {10.5120/ijca2017915564},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

WSNs are composed of many autonomous devices using sensors that are capable of interacting, processing information, and communicating wirelessly with their neighbors. Though there are many constraints in design of WSNs, the main limitation is the energy consumption. For most applications, the WSN is inaccessible or it is unfeasible to replace the batteries of the sensor nodes makes the network power inefficient. Because of this, the lifetime of the network which has maximum operational time is also reduces. To make the network power efficient, different power saving/reduction algorithms are proposed by different authors. Some of the authors have achieved the low power consumption by modifying like encryption & decryption algorithms, Routing algorithms, Energy Efficient Algorithms, Compression and decompression algorithms, minimizing control packets, and many other different power reduction algorithms. Among many algorithms, we have chosen data compression techniques aiming different targets like memory, power & bandwidth reduction. To achieve our objectives, we have worked on Huffman coding - compression algorithm and updated the algorithm by including one’s complement, XOR operations and finally named as Modified Huffman Coding. The performance of the proposed model is analyzed and it is observed that, information is maximum compressed which consumes less computational power, thereby increasing the battery life.

References

  1. B.Ruxanayasmin, B.Ananda Krishna and T.Subhashini, “Implementation of Data Compression Techniques in Mobile Ad hoc Networks”, International Journal of Computer Applications, Volume 80, No. 08, Oct.2013.
  2. Shahina Sheikh, Ms. Hemlata Dakhore, "Data Compression Techniques for Wireless Sensor Network",International Journal of Computer Science and Information Technologies, Vol. 6 (1) , 2015, 818- 821
  3. Karl Skretting, John Hakon Husøy and Sven Ole Aase, "Improved Huffman Coding Using Recursive Spitting", Article · January 1999 . Karl Skretting. 1st Karl Skretting. 18.81 · University of Stavanger (UiS).
  4. Swati C.Pakhale, et al, "Data Compression Technique Using Huffman Code for Wireless Sensor Network", International Journal Engineering Sciences & Research Technology,4(3): March, 2015.
  5. Chetna Bharat Mudgule, et al, "Data Compression in Wireless Sensor Network: A Survey", International Journal of Innovative Research in Computer and Communication Engineering, Vol. 2, Issue 11, November 2014.
  6. Peng Jiang and Sheng-Qiang Li, "A Data Compression Algorithm for Wireless Sensor Networks Based on an Optimal Order Estimation Model and Distributed Coding", Sensors 2010, 10, 9065-9083.
  7. Lecture 19, "Compression and Huffman Coding", Supplemental reading in CLRS: Section 16.3.

Keywords

WSN, Power Consumption, Security, Huffman Compression, Decompression.