Impact of Compression and Aggregation in Wireless Networks on Smart Meter Data

<p>This</p> <p>paper has investigated the performance of compression and aggregation techniques for smart meter data For large dataset sizes, the LZW algorithm</p> <p>achieved higher compression rates and consequently saves bandwidth for communication, at the cost of higher complexity The AH algorithm with lower</p> <p>processing times could save more energy, time and Hardware requirements when implemented in smart meters The trade off between compression rate,</p> <p>processing time and hardware requirement can lead us to the best selection of compression algorithm for each part of our communication scenario The double</p> <p>compression approach (scenario three) which uses the</p> <p>AH</p> <p>approach in the smart meter followed by the LZW method in the aggregator is the best choice (with 98 99 compression ratio) as the size of the</p> <p>aggregated data will increases significantly and we expect that the aggregator will have more processing power to implement the more complex LZW algorithm</p> <p>In future work, alternative compression algorithms to the LZW and AH methods should be investigated while the effect of errors and packet losses on the</p> <p>communication channels should also be considered</p> <p>References</p>