Energy Efficient Merkle Trees for Blockchains

Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This paper applies an energy-reducing algorithmic engineering technique for Merkle Tree root calculations, a principal element of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the standard and energy-reduced implementations of the Merkle Tree for different input sizes (in bytes). Our results show up to 98% reduction in energy consumption is possible within the blockchain's Merkle Tree construction module, such reductions typically increasing with larger input sizes. The proposed energy-reducing technique is similarly applicable to other key elements of blockchain computations, potentially affording even “greener” blockchain-powered systems than implied by only the Merkle Tree results obtained thus far.