Abstract

We propose DIPS (Difficulty-based Incentives for Problem Solving), a simple modification of the Bitcoin proof-of-work algorithm that rewards blockchain miners for solving optimization problems of scientific interest. The result is a blockchain which redirects some of the computational resources invested in hash-based mining towards scientific computation, effectively reducing the amount of energy ‘wasted’ on mining. DIPS builds the solving incentive directly in the proof-of-work by providing a reduction in block hashing difficulty when optimization improvements are found. A key advantage of this scheme is that decentralization is not greatly compromised while maintaining a simple blockchain design. We study two incentivization schemes and provide simulation results showing that DIPS is able to reduce the amount of hash-power used in the network while generating solutions to optimization problems.

Highlights

  • Energy spent hashing in Proof of Work (PoW) is critical for guaranteeing the integrity of transactions on a blockchain

  • We study two incentivization schemes and provide simulation results showing that DIPS is able to reduce the amount of hash-power used in the network while generating solutions to optimization problems

  • Independent Updates—We propose a second version of the protocol (DIPS) where miners are again free to submit ‘classical’ blocks with difficulty db or blocks containing a solution to an NP-complete problem, with difficulty dr

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Summary

Introduction

Energy spent hashing in Proof of Work (PoW) is critical for guaranteeing the integrity of transactions on a blockchain. ‘Useful work’ protocols can be grouped in two major types: economy-based and mining-based The former has been proposed in works such as CureCoin and Coinami which use the interest in cryptocurrencies to reward users who complete certain tasks such as DNA alignments or protein folding directly with tokens.[2,3] for the most part the blockchain protocol remains untouched and PoW is still required in its entirety, typically with some additional centralization. In the present authors’ 2017 “Proposal for a Fully Decentralized Blockchain and Proof-of-Work Algorithm for Solving NP-Complete Problems” (hereafter Oliver et al.) we observed that many scientifically relevant problems, such as protein folding, machine learning parameter searches, and DNA alignments can be phrased an NP-complete problems.[8] Since NP-complete problems preserve the property (3) there exist scientifically relevant problems that can be partially integrated into the standard PoW.

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