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Diving into Energy Use on Stellar: Blockchain Payment Efficiency Examined - SDF Blog

Significant electricity consumption of proof-of-work cryptocurrencies such as Bitcoin and Ethereum has caused critical examination of how consensus in blockchain solutions is designed. In a world with an ongoing climate crisis, substantial reduction in energy usage is required across all sectors, including the increasingly digital financial infrastructure. If a network such as Stellar is to become an integral part of the financial system’s infrastructure, it is necessary that the technology be environmentally sustainable.

In spring 2021, I studied the electricity consumption of the Stellar network, with the goal of obtaining a generalized estimate of the electricity use of a payment transaction. In this blog post, I will summarize and discuss my findings and the method used to derive them. If you’re interested in the details of the study, the full candidate thesis is available for anyone to download via the Lund University Libraries.

It is my ambition that this study can provide a step towards building a more comprehensive understanding of Stellar’s electricity consumption, while highlighting sources of uncertainty and how future studies can derive more accurate estimates. Hopefully, this can provide food for thought when it comes to how blockchains can best serve people without incurring significant energy consumption.

Background on Stellar and SCP

Stellar is a decentralized, open-membership network optimized for payments and built on blockchain technology, with the goal of enabling money to flow between banks, businesses and people across the global financial infrastructure, while minimizing latency and transaction fees. At the core of the network is a federated-voting consensus algorithm, the Stellar Consensus Protocol (SCP). Put simply, the goal of the consensus algorithm is to ensure that all nodes on the network agree on the contents of the blockchain (the ledger) without the network risking a split into two disagreeing networks ...

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