Hybrid Mining: Exploiting blockchain’s computational power for distributed problem solving

Chatterjee K, Goharshady AK, Pourdamghani A. 2019. Hybrid Mining: Exploiting blockchain’s computational power for distributed problem solving. Proceedings of the 34th ACM Symposium on Applied Computing. ACM Symposium on Applied Computing vol. Part F147772, 374–381.

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Abstract
In today's cryptocurrencies, Hashcash proof of work is the most commonly-adopted approach to mining. In Hashcash, when a miner decides to add a block to the chain, she has to solve the difficult computational puzzle of inverting a hash function. While Hashcash has been successfully adopted in both Bitcoin and Ethereum, it has attracted significant and harsh criticism due to its massive waste of electricity, its carbon footprint and environmental effects, and the inherent lack of usefulness in inverting a hash function. Various other mining protocols have been suggested, including proof of stake, in which a miner's chance of adding the next block is proportional to her current balance. However, such protocols lead to a higher entry cost for new miners who might not still have any stake in the cryptocurrency, and can in the worst case lead to an oligopoly, where the rich have complete control over mining. In this paper, we propose Hybrid Mining: a new mining protocol that combines solving real-world useful problems with Hashcash. Our protocol allows new miners to join the network by taking part in Hashcash mining without having to own an initial stake. It also allows nodes of the network to submit hard computational problems whose solutions are of interest in the real world, e.g.~protein folding problems. Then, miners can choose to compete in solving these problems, in lieu of Hashcash, for adding a new block. Hence, Hybrid Mining incentivizes miners to solve useful problems, such as hard computational problems arising in biology, in a distributed manner. It also gives researchers in other areas an easy-to-use tool to outsource their hard computations to the blockchain network, which has enormous computational power, by paying a reward to the miner who solves the problem for them. Moreover, our protocol provides strong security guarantees and is at least as resilient to double spending as Bitcoin.
Publishing Year
Date Published
2019-04-01
Proceedings Title
Proceedings of the 34th ACM Symposium on Applied Computing
Volume
Part F147772
Page
374-381
Conference
ACM Symposium on Applied Computing
Conference Location
Limassol, Cyprus
Conference Date
2019-04-08 – 2019-04-12
IST-REx-ID

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Chatterjee K, Goharshady AK, Pourdamghani A. Hybrid Mining: Exploiting blockchain’s computational power for distributed problem solving. In: Proceedings of the 34th ACM Symposium on Applied Computing. Vol Part F147772. ACM; 2019:374-381. doi:10.1145/3297280.3297319
Chatterjee, K., Goharshady, A. K., & Pourdamghani, A. (2019). Hybrid Mining: Exploiting blockchain’s computational power for distributed problem solving. In Proceedings of the 34th ACM Symposium on Applied Computing (Vol. Part F147772, pp. 374–381). Limassol, Cyprus: ACM. https://doi.org/10.1145/3297280.3297319
Chatterjee, Krishnendu, Amir Kafshdar Goharshady, and Arash Pourdamghani. “Hybrid Mining: Exploiting Blockchain’s Computational Power for Distributed Problem Solving.” In Proceedings of the 34th ACM Symposium on Applied Computing, Part F147772:374–81. ACM, 2019. https://doi.org/10.1145/3297280.3297319.
K. Chatterjee, A. K. Goharshady, and A. Pourdamghani, “Hybrid Mining: Exploiting blockchain’s computational power for distributed problem solving,” in Proceedings of the 34th ACM Symposium on Applied Computing, Limassol, Cyprus, 2019, vol. Part F147772, pp. 374–381.
Chatterjee K, Goharshady AK, Pourdamghani A. 2019. Hybrid Mining: Exploiting blockchain’s computational power for distributed problem solving. Proceedings of the 34th ACM Symposium on Applied Computing. ACM Symposium on Applied Computing vol. Part F147772, 374–381.
Chatterjee, Krishnendu, et al. “Hybrid Mining: Exploiting Blockchain’s Computational Power for Distributed Problem Solving.” Proceedings of the 34th ACM Symposium on Applied Computing, vol. Part F147772, ACM, 2019, pp. 374–81, doi:10.1145/3297280.3297319.
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