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

This paper has investigated the performance of compression and aggregation techniques for smart meter data For large dataset sizes, the LZW algorithm achieved higher compression rates and consequently saves bandwidth for communication, at the cost of higher complexity The AH algorithm with lower processing times could save more energy, time and Hardware requirements when implemented in smart meters The trade off between compression rate, processing time and hardware requirement can lead us to the best selection of compression algorithm for each part of our communication scenario The double compression approach (scenario three) which uses the AH 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 aggregated data will increases significantly and we expect that the aggregator will have more processing power to implement the more complex LZW algorithm 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 communication channels should also be considered References