Los Angeles, October 22, 2019 - Researchers and inventors Arka Ray and Jennifer Hinkel, MSc, members of the Lydion Research Alliance and founders of Blocklayer, have filed a patient application for a novel, low-energy method of blockchain proof of work called Transactional Proof of Work. Transactional Proof of Work enables confirming transactions and blocks that enable the functionalities of blockchain data structures (or distributed, sequentially linked databases) without the need for electricity-intensive, expensive computational proof of work algorithms such as those presently used for maintaining the Bitcoin and Ethereum blockchains.
“Fundamentally, Transactional Proof of Work allows us to capture the energy used in real-world transactions as a source of scarcity for the creation of, and confirmation of, ‘blocks’ in a blockchain database. This enables the creation of blockchain platforms and applications that, compared to platforms such as Bitcoin and Ethereum, are almost infinitely cheaper to run, faster and higher capacity in terms of transaction volume as the cost per transaction is so low, and immensely greener and more sustainable, as the proof of work requires no additional energy expenditure. As the inventors, we believe that this is a significant step forward for blockchain technologies that will accelerate their adoption as well as their applicability to sectors highly concerned about sustainability and cost,” said Jennifer Hinkel, co-inventor and one of the Principals of the Lydion Research Alliance.
Most blockchain platforms or protocols today, including the most well-known platforms such as Bitcoin and Ethereum, use a computational, algorithmic Proof of Work for their maintenance and “mining,” or adding new blocks of data, to the blockchain database. Transactions must be picked up and grouped into these new blocks by blockchain miners to be confirmed as part of the chain. “Miners” are essentially owners of computers where the computers race each other to be the fastest to solve a computationally difficult math problem; the fastest computer to solve the problem “wins,” receive credit (in the form of the blockchain’s cryptocurrency) for creating the block and thus confirming the transactions and data within the block, and then all of the mining computers across the network start the race again for confirmation of the next block. To be fast enough to have a chance at winning, these computers typically are using high-powered processors and graphics cards and consuming large amounts of electricity. For each Bitcoin to be mined, for example, takes an estimated 1,544 kWh of electricity, equivalent to 53 days of electricity use for a typical US household. About 900 Bitcoins are mined per day, requiring about 1.4M kWh of electricity daily; for sake of comparison, daily per-person electricity consumption in the world is about 58 kWh, so the daily consumption of the Bitcoin network is equivalent to the daily energy consumption of about 24,000 people.
The intensive energy consumption of computational Proof of Work also has geopolitical and macroeconomic implications; miners are drawn to geographies that have highly subsidized electricity prices to base their operations, including those that may have non-democratic regimes such as China, Russia, and North Korea, and miners in these regions can out-perform miners in jurisdictions that are more energy and environmentally conscious. As a result, reliance on computational Proof of Work can increasingly lead to a larger percentage of network participants being based in geographies and jurisdictions that could be unfriendly to the business interests of large multinational companies, or could put those companies at regulatory risk for economic interactions relying on jurisdictions under sanctions or other controls if their business transactions are based on computational Proof of Work networks including Bitcoin and Ethereum.
“Scientists in this field have long recognized that computational Proof of Work, while a very powerful mechanism for designing incentives to participate in a blockchain mining network, also has some inherent drawbacks, most of which are connected to electricity consumption. Computational Proof of Work therefore is more costly, slower, and more detrimental to the environment than we would like it to be. As a result, the development of alternatives, such as our discoveries around Transactional Proof of Work as well as other alternatives including Proof of Stake and other proof mechanisms will be critical in terms of making blockchain-based applications sustainable for the environment and also from a transaction cost perspective,” said co-inventor Arka Ray, Managing Principal of Blocklayer and the Lydion Research Alliance.
The full patent application can be found online here.
About the Lydion Research Alliance:
The Lydion Research Alliance is a consortium of scientists, engineers, economists, technologists, artists, and futurists dedicated to the advancement of the scientific field of Data Economics and the commercialization of Data Economic technologies.
Blocklayer LLC was formed in 2018 by the Lydion Research Alliance to develop and commercialize software platforms that enable distributed computing applications via the exchange of Lydion data assets across Data Economic Networks (or DENETs). Blocklayer’s flagship product, the Lydion Data Economic Operating System (Lydion DEOS) v0.1 is utilized globally by customers in the life sciences, banking, and cryptocurrency sectors.
About the Lydion DEOS :
The Lydion® Data Economics Operating System is the Operating System for Web3.
The Lydion® DEOS is a middleware engine used to develop distributed,decentralized applications and application platforms. By capturing energy spent in completing real-world work, The Lydion® DEOS mints digital assets called Lydions that can be utilized, shared, and transacted using secure, private Lydion Data Vaults and Networks (DENETs).
Current Lydion Engine-based applications target a combined $350B addressable market across the Health Sciences, Agriculture, Climate, Industrials, Fintech, Personal Data, Gaming, and Education sectors.