Distributed Rational Consensus

The \textit{consensus} is a very important problem in distributed computing, where among the $n$ players, the honest players try to come to an agreement even in the presence of $t$ malicious players. In game theoretic environment, \textit{the group choice problem} is similar to the \textit{rational consensus problem}, where every player $p_i$ prefers come to consensus on his value $v_i$ or to a value which is as close to it as possible. All the players need to come to an agreement on one value by amalgamating individual preferences to form a group or social choice. In rational consensus problem, there are no malicious players. We consider the rational consensus problem in the presence of few malicious players. The players are assumed to be rational rather than honest and there exist few malicious players among them. Every rational player primarily prefers to come to consensus on his value and secondarily, prefers to come to consensus on other player\u27s value. In other words, if $w_1$, $w_2$ and $w_3$ are the payoffs obtained when $p_i$ comes to consensus on his value, $p_i$ comes to consensus on other\u27s value and $p_i$ does not come to consensus respectively, then $w_1 > w_2 > w_3$. We name it as \textit{distributed rational consensus problem} DRC. The players can have two values, either 1 or 0, i.e binary consensus. The rational majority is defined as number of players, who wants to agree on one particular value, and they are more than half of the rational players. Similarly rational minority can be defined. We have considered EIG protocol, and characterized the rational behaviour, and shown that EIG protocol will not work in rational environment. We have proved that, there exists no protocol, which solves distributed consensus problem in fixed running time, where players have knowledge of other players values during the protocol. This proof is based on Maskin\u27s monotonicity property. The good news is, if the players do not have knowledge about other players values, then it can be solved. This can be achieved by verifiable rational secret sharing, where players do not exchange their values directly, but as pieces of it

The Authority of Distributed Consensus Systems Trust, Governance, and Normative Perspectives on Blockchains and Distributed Ledgers

The subjects of this dissertation are distributed consensus systems (DCS). These systems gained prominence with the implementation of cryptocurrencies, such as Bitcoin. This work aims at understanding the drivers and motives behind the adoption of this class of technologies, and to – consequently – evaluate the social and normative implications of blockchains and distributed ledgers. To do so, a phenomenological account of the field of distributed consensus systems is offered, then the core claims for the adoption of systems are taken into consideration. Accordingly, the relevance of these technologies on trust and governance is examined. It will be argued that the effects on these two elements do not justify the adoption of distributed consensus systems satisfactorily. Against this backdrop, it will be held that blockchains and similar technologies are being adopted because they are regarded as having a valid claim to authority as specified by Max Weber, i.e., herrschaft. Consequently, it will be discussed whether current implementations fall – and to what extent – within the legitimate types of traditional, charismatic, and rational-legal authority. The conclusion is that the conceptualization developed by Weber does not capture the core ideas that appear to establish the belief in the legitimacy of distributed consensus systems. Therefore, this dissertation describes the herrschaft of systems such as blockchains by conceptualizing a computational extension of the pure type of rational-legal authority, qualified as algorithmic authority. The foundational elements of algorithmic authority are then discussed. Particular attention is focused on the idea of normativity cultivated in systems of algorithmic rules as well as the concept of decentralization. Practical suggestions conclude the following dissertation

Agent-Based Simulations of Blockchain protocols illustrated via Kadena's Chainweb

While many distributed consensus protocols provide robust liveness and consistency guarantees under the presence of malicious actors, quantitative estimates of how economic incentives affect security are few and far between. In this paper, we describe a system for simulating how adversarial agents, both economically rational and Byzantine, interact with a blockchain protocol. This system provides statistical estimates for the economic difficulty of an attack and how the presence of certain actors influences protocol-level statistics, such as the expected time to regain liveness. This simulation system is influenced by the design of algorithmic trading and reinforcement learning systems that use explicit modeling of an agent's reward mechanism to evaluate and optimize a fully autonomous agent. We implement and apply this simulation framework to Kadena's Chainweb, a parallelized Proof-of-Work system, that contains complexity in how miner incentive compliance affects security and censorship resistance. We provide the first formal description of Chainweb that is in the literature and use this formal description to motivate our simulation design. Our simulation results include a phase transition in block height growth rate as a function of shard connectivity and empirical evidence that censorship in Chainweb is too costly for rational miners to engage in. We conclude with an outlook on how simulation can guide and optimize protocol development in a variety of contexts, including Proof-of-Stake parameter optimization and peer-to-peer networking design.Comment: 10 pages, 7 figures, accepted to the IEEE S&B 2019 conferenc