An evaluation of compression techniques for Wireless Sensor Networks

Wireless sensor networks (WSN) typically consist of compact, low energy devices capable of sustaining a variety of ad-hoc topologies and operate for many years from a single, non-renewable, finite energy source such as a battery. This limitation in energy has led to much research in the field of energy conservation both through hardware and software techniques. The transmission of data incurs the highest energy cost in a WSN device and this study sets out to investigate different types of software compression techniques suitable for resource limited hardware, with the aim to minimize the energy required to transmit the data. An obvious trade-off exists between the computational energy used for compression versus the saving in energy associated with the transmission of compressed data instead of raw data. It is shown that lossless techniques could not sustain a fixed compression ratio when presented data with significant fluctuations and the study then considered lossy techniques for alternative compression methods. In addition, this study introduces a hybrid technique designed specifically for WSN devices and is shown to support other lossy techniques by further data reduction. The results from this study show that data reduction is possible when selectively implementing compression techniques best suited to application specific data, whilst being sensitive to the limited resources available.