Difficulty Scaling in Proof of Work for Decentralized Problem Solving

  • Pericles Philippopoulos Ozeki Inc.
  • Alessandro Ricottone McGill University
  • Carlos G. Oliver Ozeki Inc.
Keywords: Proof of work, optimization, blockchain


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.

Author Biographies

Pericles Philippopoulos, Ozeki Inc.

PhD Candidate, Department of Physics, McGill University

Co-founder Ozeki Inc. Blockchain Research & Consulting

Alessandro Ricottone, McGill University
PhD Candidate, Department of Physics, McGill University
Carlos G. Oliver, Ozeki Inc.

PhD Candidate, Computer Science

McGill University & Montreal Institute for Learning Algorithms

Co-founder Ozeki Inc. Blockchain Research & Consulting


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How to Cite
Philippopoulos, P., Ricottone, A., & G. Oliver, C. (2020). Difficulty Scaling in Proof of Work for Decentralized Problem Solving. Ledger, 5. https://doi.org/10.5195/ledger.2020.194
Research Articles