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 thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements 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) and of the Proof of Work for different difficulty levels. Our results show up to 98\% reduction in energy consumption is possible within the blockchain\u27s Merkle Tree construction module, such reductions typically increasing with larger input sizes. For Proof-of-Work calculations, our results show an average energy reduction of 20\% across typical difficulty levels. The proposed energy-reducing technique is potentially applicable to other key elements of blockchain computations, potentially affording even greener blockchain-powered systems than implied by only the Merkle Tree and Proof of Work results obtained thus far
