30 research outputs found
Blockchain Mining Games with Pay Forward
We study the strategic implications that arise from adding one extra option
to the miners participating in the bitcoin protocol. We propose that when
adding a block, miners also have the ability to pay forward an amount to be
collected by the first miner who successfully extends their branch, giving them
the power to influence the incentives for mining. We formulate a stochastic
game for the study of such incentives and show that with this added option,
smaller miners can guarantee that the best response of even substantially more
powerful miners is to follow the expected behavior intended by the protocol
designer
Pandora's Box Problem with Order Constraints
The Pandora's Box Problem, originally formalized by Weitzman in 1979, models
selection from set of random, alternative options, when evaluation is costly.
This includes, for example, the problem of hiring a skilled worker, where only
one hire can be made, but the evaluation of each candidate is an expensive
procedure. Weitzman showed that the Pandora's Box Problem admits an elegant,
simple solution, where the options are considered in decreasing order of
reservation value,i.e., the value that reduces to zero the expected marginal
gain for opening the box. We study for the first time this problem when order -
or precedence - constraints are imposed between the boxes. We show that,
despite the difficulty of defining reservation values for the boxes which take
into account both in-depth and in-breath exploration of the various options,
greedy optimal strategies exist and can be efficiently computed for tree-like
order constraints. We also prove that finding approximately optimal adaptive
search strategies is NP-hard when certain matroid constraints are used to
further restrict the set of boxes which may be opened, or when the order
constraints are given as reachability constraints on a DAG. We complement the
above result by giving approximate adaptive search strategies based on a
connection between optimal adaptive strategies and non-adaptive strategies with
bounded adaptivity gap for a carefully relaxed version of the problem
SoK:Blockchain governance
Blockchain systems come with a promise of decentralization that, more often than not, stumbles on a roadblock when key decisions about modifying the software codebase need to be made. In a setting where "code-is-law," modifying the code can be a controversial process, frustrating to system stakeholders, and, most crucially, highly disruptive for the underlying systems. This is attested by the fact that both of the two major cryptocurrencies, Bitcoin and Ethereum, have undergone "hard forks" that resulted in the creation of alternative systems which divided engineering teams, computational resources, and duplicated digital assets creating confusion for the wider community and opportunities for fraudulent activities. The above events, and numerous other similar ones, underscore the importance of Blockchain governance, namely the set of processes that blockchain platforms utilize in order to perform decision-making and converge to a widely accepted direction for the system to evolve. While a rich topic of study in other areas, including social choice theory and electronic voting for public office elections, governance of blockchain platforms is lacking a well established set of methods and practices that are adopted industry wide. Instead, different systems adopt approaches of a variable level of sophistication and degree of integration within the platform and its functionality. This makes the topic of blockchain governance a fertile domain for a thorough systematization that we undertake in this work.Our methodology starts by distilling a comprehensive array of properties for sound governance systems drawn from academic sources as well as grey literature of election systems and blockchain white papers. These are divided into seven categories, suffrage, Pareto efficiency, confidentiality, verifiability, accountability, sustainability and liveness that capture the whole spectrum of desiderata of governance systems. We interpret these properties in the context of blockchain platforms and proceed to classify ten block-chain systems whose governance processes are sufficiently well documented in system white papers, or it can be inferred by publicly available information and software. While all the identified properties are satisfied, even partially, by at least one system, we observe that there exists no system that satisfies most properties. Our work lays out a common foundation for assessing governance processes in blockchain systems and while it highlights shortcomings and deficiencies in currently deployed systems, it can also be a catalyst for improving these processes to the highest possible standard with appropriate trade-offs, something direly needed for blockchain platforms to operate effectively in the long term
The Infinite Server Problem
We study a variant of the k-server problem, the infinite server problem, in which infinitely many servers reside initially at a particular point of the metric space and serve a sequence of requests. In the framework of competitive analysis, we show a surprisingly tight connection between this problem and the (h,k)-server problem, in which an online algorithm with k servers competes against an offline algorithm with h servers. Specifically, we show that the infinite server problem has bounded competitive ratio if and only if the (h,k)-server problem has bounded competitive ratio for some k=O(h). We give a lower bound of 3.146 for the competitive ratio of the infinite server problem, which implies the same lower bound for the (h,k)-server problem even when k>>h and holds also for the line metric; the previous known bounds were 2.4 for general metric spaces and 2 for the line. For weighted trees and layered graphs we obtain upper bounds, although they depend on the depth. Of particular interest is the infinite server problem on the line, which we show to be equivalent to the seemingly easier case in which all requests are in a fixed bounded interval away from the original position of the servers. This is a special case of a more general reduction from arbitrary metric spaces to bounded subspaces. Unfortunately, classical approaches (double coverage and generalizations, work function algorithm, balancing algorithms) fail even for this special case
Reallocating Multiple Facilities on the Line
We study the multistage -facility reallocation problem on the real line,
where we maintain facility locations over stages, based on the
stage-dependent locations of agents. Each agent is connected to the nearest
facility at each stage, and the facilities may move from one stage to another,
to accommodate different agent locations. The objective is to minimize the
connection cost of the agents plus the total moving cost of the facilities,
over all stages. -facility reallocation was introduced by de Keijzer and
Wojtczak, where they mostly focused on the special case of a single facility.
Using an LP-based approach, we present a polynomial time algorithm that
computes the optimal solution for any number of facilities. We also consider
online -facility reallocation, where the algorithm becomes aware of agent
locations in a stage-by-stage fashion. By exploiting an interesting connection
to the classical -server problem, we present a constant-competitive
algorithm for facilities
Multi-unit Bilateral Trade
We characterise the set of dominant strategy incentive compatible (DSIC),
strongly budget balanced (SBB), and ex-post individually rational (IR)
mechanisms for the multi-unit bilateral trade setting. In such a setting there
is a single buyer and a single seller who holds a finite number k of identical
items. The mechanism has to decide how many units of the item are transferred
from the seller to the buyer and how much money is transferred from the buyer
to the seller. We consider two classes of valuation functions for the buyer and
seller: Valuations that are increasing in the number of units in possession,
and the more specific class of valuations that are increasing and submodular.
Furthermore, we present some approximation results about the performance of
certain such mechanisms, in terms of social welfare: For increasing submodular
valuation functions, we show the existence of a deterministic 2-approximation
mechanism and a randomised e/(1-e) approximation mechanism, matching the best
known bounds for the single-item setting
Would Friedman Burn your Tokens?
Cryptocurrencies come with a variety of tokenomic policies as well as
aspirations of desirable monetary characteristics that have been described by
proponents as 'sound money' or even 'ultra sound money.' These propositions are
typically devoid of economic analysis so it is a pertinent question how such
aspirations fit in the wider context of monetary economic theory. In this work,
we develop a framework that determines the optimal token supply policy of a
cryptocurrency, as well as investigate how such policy may be algorithmically
implemented. Our findings suggest that the optimal policy complies with the
Friedman rule and it is dependent on the risk free rate, as well as the growth
of the cryptocurrency platform. Furthermore, we demonstrate a wide set of
conditions under which such policy can be implemented via contractions and
expansions of token supply that can be realized algorithmically with block
rewards, taxation of consumption and burning the proceeds, and blockchain
oracles