Edge Hill University
Mehdi Zeinali-Research Poster.pdf (538.15 kB)

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

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posted on 2023-01-19, 15:21 authored by MEHDI ZEINALI, John Thompson


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


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



This work supported through the ADVANTAGE project from the European Unions Seventh Framework Programme for research, by grant agreement no. 607774.


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