Abstract—A major performance bottleneck in sensor networks is energy since it is impractical to replace the batteries in embedded sensor nodes post-deployment so (Wireless Sensor Networks) WSNs are energy constrained. Radio transmission is most energy draining task that a node performs. Data aggregation and data compression are the widely discussed cases to save a single nodes’ lifetime by reducing data to be transmitted but as the memory and computational resources are very limited, these tasks must be performed efficaciously. Here we present a modified version of data compression algorithm presented by Francesco Marcelloni in IEEE Communications Letters 2008. The algorithm Marcelloni presented performs best on variables having a trend of reading implying having least fluctuation with previous reading but as the data fluctuates, the trend vanishes and algorithm becomes inefficacious. We add a pseudo-trend to those fluctuating data on referred algorithm and make it more efficacious on such scenarios. Our experimental results are shown in this article explaining how the existing algorithm, that is referred to, cannot perform its best at those conditions and how our modified algorithm outperforms.
Index Terms—Data compression, wireless sensor network, in-network data aggregation.
The authors are with Shanghai Ocean University, Shanghai, China (email: linkpawan@gmail.com, pun_uma@yahoo.com, mchen@shou.edu.cn).
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Cite:Pawan Acharya, Uma Pun, and Chen Ming, "An Efficient Lossless Data Compression Algorithm for Fluctuating Environment Variables in WSN," International Journal of Future Computer and Communication vol. 3, no. 4, pp. 232-236, 2014.
