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Oceanic Games: Centralization Risks and Incentives in Blockchain Mining

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Mathematical Research for Blockchain Economy

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

Abstract

To participate in the distributed consensus of permissionless blockchains, prospective nodes—or miners—provide proof of designated, costly resources. However, in contrast to the intended decentralization, current data on blockchain mining unveils increased concentration of these resources in a few major entities, typically mining pools. To study strategic considerations in this setting, we employ the concept of Oceanic Games [27]. Oceanic Games have been used to analyze decision making in corporate settings with small numbers of dominant players (shareholders) and large numbers of individually insignificant players, the ocean. Unlike standard equilibrium models, they focus on measuring the value (or power) per entity and per unit of resource in a given distribution of resources. These values are viewed as strategic components in coalition formations, mergers and resource acquisitions. Considering such issues relevant to blockchain governance and long-term sustainability, we adapt oceanic games to blockchain mining and illustrate the defined concepts via examples. The application of existing results reveals incentives for individual miners to merge in order to increase the value of their resources. This offers an alternative perspective to the observed centralization and concentration of mining power. Beyond numerical simulations, we use the model to identify issues relevant to the design of future cryptocurrencies and formulate prospective research questions.

Stefanos Leonardos and Georgios Piliouras acknowledge that this work was supported in part by the National Research Foundation (NRF), Prime Minister’s Office, Singapore, under its National Cybersecurity R&D Programme (Award No. NRF2016NCR-NCR002-028) and administered by the National Cybersecurity R&D Directorate. Georgios Piliouras acknowledges SUTD grant SRG ESD 2015 097, MOE AcRF Tier 2 Grant 2016-T2-1-170 and NRF 2018 Fellowship NRF-NRFF2018-07.

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Notes

  1. 1.

    In terms of market capitalization, cf. coinmarketcap.com.

  2. 2.

    The notation is common in the literature of weighted voting games, see [25, 31, 32] for a more related application. Also, in most cases, we will be interested in \(q=0.5\) or 50% but the current model applies to any q of interest.

  3. 3.

    For more details and the probabilistic derivation of these values, we refer to [27].

  4. 4.

    Due to continuity properties, there is no difference between using the q \(=\) 50% quota or symbolically, the q \(=\) 51% quota, as is common in the related literature [11, 22, 28].

  5. 5.

    This statement actually holds for any quota \(q\in \left( 0,1\right) \) and not only for \(q=0.5\) as formulated here.

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Authors and Affiliations

  1. National and Kapodistrian University of Athens, Panepistimioupolis, 161 22, Zografou, Greece

    Nikos Leonardos

  2. Singapore University of Technology and Design, 8 Somapah Rd, Singapore, 487372, Singapore

    Stefanos Leonardos & Georgios Piliouras

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  1. Nikos Leonardos
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Correspondence to Stefanos Leonardos .

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Editors and Affiliations

  1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos Pardalos

  2. Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias Kotsireas

  3. Data Science Institute, Imperial College London, London, UK

    Yike Guo

  4. Department of Computing, Imperial College London, London, UK

    William Knottenbelt

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Leonardos, N., Leonardos, S., Piliouras, G. (2020). Oceanic Games: Centralization Risks and Incentives in Blockchain Mining. In: Pardalos, P., Kotsireas, I., Guo, Y., Knottenbelt, W. (eds) Mathematical Research for Blockchain Economy. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-37110-4_13

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