Fairness and Efficiency in DAG-Based Cryptocurrencies

Birmpas, Georgios; Koutsoupias, Elias; Lazos, Philip; Marmolejo-Cossío, Francisco J.

doi:10.1007/978-3-030-51280-4_6

Cited by 10 publications

(4 citation statements)

References 17 publications

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“…They showed that many existing protocols were vulnerable to the greedy strategy where a participant always selects the transaction that maximizes its reward. Birmpas et al [4] proposed a new theoretical framework that captures a large family of DAG-based ledger implementations and showed how fairness and efficiency suffer from high transaction rates despite all agents behaving honestly in a given DAG-based ledger. The performance of DAG-based DLTs has also been studied by Cao et al [9].…”

Section: Related Workmentioning

confidence: 99%

Computing the Heaviest Conflict-free Sub-DAG in DAG-based DLTs

Bramas

2024

Distrib. Ledger Technol.

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In this paper, we consider DAG-based Distributed Ledger Technologies (DLTs), i.e. , DLTs where each block can reference several previous blocks hence forming a Directed Acyclic Graph of Blocks (BDAG). Each block has a weight (usually a constant normalized to one) and our goal is to compute the heaviest sub-BDAG that does not contain conflicting blocks. First, we prove that computing such a sub-BDAG is NP-complete. Then, we show that the difficulty comes from concurrent conflicts and we present an optimal algorithm that is polynomial if the number of concurrent conflicts is bounded. We also give an efficient incremental version of our algorithm. Finally, we evaluate the performance of our algorithm on random BDAGs against an existing algorithm called GHOSTDAG and show that, in addition to being optimal, our algorithm is also more efficient in practice.

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Section: Related Workmentioning

confidence: 99%

Computing the Heaviest Conflict-free Sub-DAG in DAG-based DLTs

Bramas

2024

Distrib. Ledger Technol.

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“…[7,22,18,9,12,3,14]. Recently, there have been efforts in studying variations of the blockchain protocol and to analyze the impact in terms of mining incentives [5,20].…”

Section: Related Literaturementioning

confidence: 99%

“…By February 2021, the value of 1 BTC was close to 47000 USD 4 and the social energy consumption per year for Bitcoin mining has been estimated in 77.78 TWh per year. 5 Assuming the hash power of a player to be proportional to the energy consumption, and that the price of a kWh is 0.01 USD, we estimate the marginal costs of each i ∈ {1, 2} as c i ≈ 0.01/(6.25 • 4.7 • 10 4 ) × (77.78 • 10 9 )/(365 • 24 • 60) × p i ≈ 0.005p i [units/min]. When both players try to maximize their asymptotic expected revenue neglecting their costs, by Corollary 1, Frontier is a Nash equilibrium.…”

Section: A Market Share Case Studymentioning

confidence: 99%

The Convergence Rates of Blockchain Mining Games: A Markovian Approach

Jofré¹,

Pardo²,

Salas³

et al. 2021

Preprint

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Understanding the strategic behavior of miners in a blockchain is of great importance for its proper operation. A common model for mining games considers an infinite time horizon, with players optimizing asymptotic average objectives. Implicitly, this assumes that the asymptotic behaviors are realized at human-scale times, otherwise invalidating current models. We study the mining game utilizing Markov Decision Processes. Our approach allows us to describe the asymptotic behavior of the game in terms of the stationary distribution of the induced Markov chain. We focus on a model with two players under immediate release, assuming two different objectives: the (asymptotic) average reward per turn and the (asymptotic) percentage of obtained blocks.Using tools from Markov chain analysis, we show the existence of a strategy achieving slow mixing times, exponential in the policy parameters. This result emphasizes the imperative need to understand convergence rates in mining games, validating the standard models. Towards this end, we provide upper bounds for the mixing time of certain meaningful classes of strategies. This result yields criteria for establishing that long-term averaged functions are coherent as payoff functions. Moreover, by studying hitting times, we provide a criterion to validate the common simplification of considering finite states models. For both considered objectives functions, we provide explicit formulae depending on the stationary distribution of the underlying Markov chain. In particular, this shows that both mentioned objectives are not equivalent. Finally, we perform a market share case study in a particular regime of the game. More precisely, we show that an strategic player with a sufficiently large processing power can impose negative revenue on honest players.

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“…There is a growing appreciation that incentivisation is not only important, but necessary, to ensure the successful instantiation of an SMR protocol. Many papers have argued for the incentivisation of players in SMR protocols [2,5,9,10,15,17,22,23,25,26,30,31,32] while many other papers demonstrate the critical need for incentive compatibility in tokenised SMR protocols [4,7,8,11,12,13,20,21,27,28].…”

Section: Related Workmentioning

confidence: 99%

Achieving State Machine Replication without Honest Players

McMenamin¹,

Daza²,

Pontecorvi³

2020

Preprint

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State machine replication protocols have reached a crucial juncture in their widespread deployment. Tokenised state machine replication protocols, which utilise an internal token for rewarding player participation, have brought about major advances in the areas of finance, internet of things, supply chain, legal systems, and data storage, to name but a few. However, the viability of these protocols as replacements for their centralised alternatives requires guarantees of player actions at all times which at present do not exist. Current standards for player characterisation in tokenised state machine replication protocols allow for honest players who will always follow the protocol, regardless of possible token increases for deviating. Given the ever-increasing market capitalisation of these tokenised protocols, honesty is becoming more expensive and more unrealistic. As such, this out-dated player characterisation must be removed to provide true guarantees of safety and liveness in a major stride towards universal trust in state machine replication protocols and a new scale of adoption. As all current state machine replication protocols are built on these legacy standards, it is imperative that a new player model is identified and utilised to reflect the true nature of players in tokenised protocols, now and into the future.To this effect, we propose the ByRa player model for state machine replication protocols. In the ByRa model, players either attempt to maximise their tokenised rewards, or behave adversarially. This merges the fields of game theory and distributed systems, an intersection in which tokenised state machine replication protocols exist, but on which little formalisation has been carried out. In the ByRa model, we identify the properties of strong incentive compatibility in expectation and fairness that all protocols must satisfy in order to achieve state machine replication. We then provide FAIRSICAL, a protocol which provably satisfies these properties, and by doing so, achieves state machine replication in the ByRa model.

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Fairness and Efficiency in DAG-Based Cryptocurrencies

Cited by 10 publications

References 17 publications

Computing the Heaviest Conflict-free Sub-DAG in DAG-based DLTs

Computing the Heaviest Conflict-free Sub-DAG in DAG-based DLTs

The Convergence Rates of Blockchain Mining Games: A Markovian Approach

Achieving State Machine Replication without Honest Players

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