Compressão de Dados em Redes de Sensores sem Fio Usando Codificação de Huffman

This work presents a lightweight data compression method for wireless sensor networks. Instead of attempting to devise novel ad-hoc mechanisms to solve the problem, we attempt to show that, given previous general knowledge of the parameters that must be monitored, it is possible to efficiently employ conventional Huffman coding to represent the same phenomenon when measured at a different location and time period. The statistics of the parameter which must be monitored can be inferred, for example, from public datasets. The Huffman dictionary computed using those statistics is shown to approach the entropy of the data difference. Experimental results with temperature datasets show that the proposed method outperforms one of the most popular compression mechanisms for sensor networks.