1. Introduction
Governance models of blockchain platforms are becoming increasingly important, as they can meaningfully affect the platform attractiveness and the users’ participation. For many blockchains, a main concern related to governance appears to be the possible emergence of dominant positions, that is of subjects who could keep under their control a large number of votes, possibly even the majority of votes, and therefore the platform evolution. Indeed, this may discourage users with small number of votes from participating in governance, perhaps inducing them to drop out of the platform. For this reason, a voting method, which in recent years has gained some attention for social decisions in general, hence also as a possible solution to the above problem in blockchain platforms, is quadratic voting (QV) [
1,
2,
3,
4,
5,
6,
7,
8,
9] Its interest is additionally testified by an analogous quadratic criterion, which has recently been proposed for project co-funding [
10]. In its most common application, represented by a voting session with a list of binary items to vote of the type
, QV allows participants to express both the
direction as well as the intensity of one’s preferences as it takes place, for example, with oral acclamation [
1,
2,
3,
4,
5]. For this reason, unlike the standard
majority voting, QV sets up a framework where minority voters, that is those subjects with a limited number of votes, could still have chances to obtain the desirable outcomes for those issues which they care particularly about. Concern for. and protection of, such minorities would clearly make sense when a relatively small number of votes is not due to a user’s lack of interest in the voted issues.
The main reason for this to take place is how available votes are considered in a QV session, where a session is composed of a sequence of voting rounds (items). More specifically, the number of votes available to a subject represents her budget of votes for the session, which cannot be lower than the total cost of using the votes in the various rounds. For every round, such cost is assumed to be quadratic in the number of votes chosen for the item, and the total cost of the voting session cannot exceed the total number of available votes. Frequently, in the literature, the cost of voting is indeed expressed in monetary terms, rather than by a number of votes. However, in PoS-blockchain-based platforms, these two interpretations coincide, since the budget of votes is given by the monetary stake.
As an illustration of QV, assume an individual has votes available to participate in a voting session with two items under scrutiny. Suppose that in the first item, the decision is between , and in the second item, it is between , where and may simply be, respectively, and . Moreover, suppose also that cares more about the first item than about the second item. Therefore, with QV, they could decide to use, for example, votes when voting for the first item and vote when voting for the second item, so that such distribution of votes will satisfy . That is, is the available budget of votes, while is the cost of using votes in the first round and the cost of using one vote in the second round. Therefore, with QV, the marginal cost of the vote is which is equal to twice as much the ordinal number of votes minus . Hence, for instance, the marginal cost of the first vote is while the marginal cost of the second vote is and so on. It follows that the most expensive vote for a user is the marginal (last) one.
Consider now another individual with a total number of votes equal to , hence much less than , with caring about the outcome of the second item only. Then, could decide to allocate votes to the first item, basically avoiding voting, and votes to the second item, so that her budget of votes is satisfied, . Therefore, may have good chances of affecting the voting outcome of the second item in a way desirable for her. With only two individuals and only two items of the above example, if decisions within each round are taken according to the majority criterion then, with QV, individual could guarantee for herself the most desirable voting outcome in the second round.
Instead, if the voting protocol were the standard majority voting, where individuals use all of their votes in each round, then will secure for herself the best outcome in both items, having votes against . This, of course, does not mean that what is desirable for is necessarily unwanted by . Indeed, their preferences may certainly be aligned, in which case the voting protocol would be irrelevant. However, since this is more of an exception than the rule, with QV the user with a lower budget of votes could have a higher chance to obtain the desirable outcome, at least for those items that they care particularly about.
The above numerical example identifies one important point. That is, the timing with which users communicate to the platform how many votes they intend to use in each round can be very important. For example, if voters need to reveal simultaneously, at the very beginning of the voting session, how many votes they want to allocate to each item, then the reasoning in the above example can make sense. However if instead , for instance, before voting could be allowed to know the votes assignment across the two rounds decided by , then could perhaps assign just 1 vote to the first item and votes to the second, obtaining her most preferred outcome in both voting sessions. This point will be discussed in more detail later in the paper.
There could be protocols other than QV for
protecting minority voters. Therefore, it is natural to ask which properties QV enjoys as compared to alternative voting criteria. One reason is certainly given by analytical simplicity and tractability of quadratic functions. Though attractive, this however would not be a strong enough motivation for choosing QV rather than, for example, cubic voting. [
1,
2] point out that, as a
vote pricing rule, QV enjoys the main property of being
robustly optimal. Broadly speaking, this means that whatever is the users’ probability of winning a voting round in their model, QV ensures that the most desirable
social outcome will receive the highest number of votes; alternatively, that the number of votes assigned by a user to an item is proportional to (a linear function of) the utility/value of the item.
In this work, we investigate QV as applied to the governance of PoS-based blockchain platforms, by assuming that a user’s
stake represents her budget of votes in a voting session. Taking such budget as given, the paper first considers some alternative definitions of the success probability in single voting rounds, to provide closed forms for the optimal number of votes to be allocated to the relevant items under voting. The analysis is game theoretic, and the optimal number of votes is characterized as a Nash Equilibrium of the game. To the best of our knowledge, no such contribution exists in the literature. We then extend the analysis to a general formulation of the success probability. Additionally, we also investigate one of the main concerns in blockchain voting procedures. That is, when users are anonymous, they may decide to split their monetary holdings, hence their stakes, into several accounts to increase their chances of successful voting. This is well known in the literature as the
Sybil attack [
11,
12], indeed characterized by users taking multiple identities. Moreover, we discuss if and how the voting timing can affect the outcome of the elections. The paper is structured as follows. In
Section 2, we introduce the model fundamentals and provide a symmetric Nash Equilibrium characterization of the optimal number of votes in each round. In
Section 3, we discuss whether or not QV may represent an incentive for users to engage in Sybil attacks, while
Section 4 considers the implication of simultaneous versus sequential votes selection in the various rounds. In
Section 5, we consider a more detailed description of the users’ preferences, while
Section 6 concludes the paper.
2. The Framework
In this initial section, we introduce a framework to investigate the optimal number of votes with QV in proof-of-stake-based blockchains.
We begin assuming that is the number of committee members in a voting session and their stakes, typically defined by a number of currency units. Henceforth, , with , will be considered as already chosen by the users and a given in the analysis.
We assume a voting session takes place over a time interval, and it is defined by a sequence of voting rounds, one for each item under consideration. Each vote is binary, that is, it has two alternatives: or , where could also simply mean disapproval of .
Let be the total number of voting rounds, which we also refer to as issues/items to be voted in the same session, and suppose , with and , is the (reserve) value assigned by user to round .
That is, we define to be the maximum number of currency units that member is willing to pay for the most desirable alternative , in the th voting session. To simplify, without losing much in generality, we also assume that for each user, the least desirable of the two options under voting has value. Therefore, represents the maximum utility that user can obtain when voting for issue .
Hence, if
is the stake of the generic
user
with QV, the total number of votes available in the
rounds of a voting session is equal to
where
is the number of currency units, i.e., votes, allocated to round
.
For example, suppose . Then, is the number of votes adopted by the user, and therefore, is agent distribution of the total votes over the four issues under voting. In what follows, to simplify the exposition, without much loss of generality, we shall also consider the possibility of fractional, non-integer votes.
The quantity is also interpreted as the cost of using votes in round while as the budget of votes available for the entire voting session.
Therefore, at a general level,
for given the optimal
could be defined as the solution to the following problem
where
is user
probability of obtaining value
and
the profile of stakes chosen by the committee members other than user
in round
. More specifically, if
is the profile of stakes in round
then
.
It seems reasonable to assume to be increasing with respect to , while its behaviour with respect to may vary according to whether or not the other committee members would vote as agent .
The optimal choice of can depend upon several elements. In particular, it could depend on whether the chosen is communicated sequentially by the users to the platform, round by round, or “simultaneously” at the very beginning of the session for all . Moreover, in general, would be chosen within a game theoretic context with strategic interaction and would therefore also depend upon .
In what follows, we begin the analysis considering a very simple case, where users choose independently of each other, “simultaneously”, in a game with complete information over the other users’ values. More specifically, will be selected by users at the beginning of the session and independently communicated to the platform.
2.1. A Benchmark Framework with Simultaneous Selection of
In this paragraph, we assume that users vote independently of each other and know each other’s value. This is clearly a strong assumption, which nevertheless may become more realistic when voters are not strangers to each other. To gain some initial insights, as a very first step in the analysis, we introduce the following expression for the success probability:
where
is the total number of votes in the committee used in round
and
is the probability that
will obtain the value
in the
voting round. The above definition captures the idea that the committee members vote independently of each other and that they consider the
worst case, where the success probability decreases with the number of members’ votes other than
.
Admittedly, assuming
may be a simplification of what occurs in reality, since other users may cast the same vote as the
member. However, as an initial approximation, we find the probability definition to be acceptable. A more detailed discussion on users’ preferences is deferred until
Section 5.
It follows that the above problem becomes
Problem (1), in terms of the associated Lagrange function, can be formulated as follows:
With no major loss of generality, treating
as a continuous variable for convenience and considering the first-order condition with respect to
, derived from expression (2), we obtain
where
is the Lagrange multiplier associated with constraint
Before proceeding, it is worth noticing that, unlike what occurs in [
1,
2] in expression (3), the chosen stake
is not a linear but rather a non-linear function of
. This is due to our assumption of the success probability
, which is indeed introducing the non-linearity in expression (3). Below, in
Section 2.5.1, we shall discuss a case with a linear relation between
and
.
Expression (3) clarifies that a user’s optimal stake level also depends on the other committee members’ profile of stakes , which implies that the selection of the optimal across agents could be modeled as a game. Indeed, expression (3) provides the best reply correspondence of each user, which explicitly depends on the other users’ number of votes.
Below, we state the first result, which represents a benchmark for the rest of the analysis.
Proposition 1. Suppose and, for alland all. Then, there exists a unique symmetric pure strategy Nash Equilibrium of the game with complete information,, given bywhere is each user’s total value in the voting session. Proof. Immediate. Since
and
, it is
for all
. Hence, it follows that expression (3) can be re-written as
and therefore
Thus, summing up both sides of expression (6) with respect to
, we obtain
Finally, replacing obtained from expression (7), into expression (5), the result follows. □
Expression (4) captures some main intuitions of a symmetric equilibrium, in that the optimal number of votes assigned to an item is proportional to its importance , representing such share of the total stake . Since expression (4) is the same for all committee members, then the probability that an issue is voted according to the preferences of a user is , while user’s expected utility given by . Finally, notice also that is an increasing and concave function with respect to , a shape due to both the probability assumption and to QV.
If Proposition 1 presents an explicit result, for our specific assumption of the success probability, it is also true that it is a benchmark, a limit case, since it is unlikely for reality to be so nicely symmetric. Yet, as we discuss below, computing explicit solutions of under asymmetric values and stakes can be rather cumbersome. However, before doing so, in what follows, we explore the first simple extension of QV.
2.4. An Asymmetric Model with Simultaneous Choice
We now discuss how much more involved the optimal determination of becomes with asymmetric users, that is when values and stakes may differ across committee members. As we shall see, values and stakes can interact in a complex way in the expression of .
To do so, we consider the simplest case in which
and
, still assuming
It follows immediately that the first-order condition (3) for, respectively,
becomes
Dividing the left-hand side and right-hand side of (i) by (ii), we obtain
Likewise, dividing (iii) by (iv), we obtain
Replacing expression (15) into expression (16) leads to
Expression (17) clarifies that the proportion between the total number of votes dedicated to the first and second item depends exclusively upon the users’ values. In particular, if then the total amount of votes will be the same in each of the two items. This is so, for example, if and that is, if the values’ ratio for a user is the inverse of the values’ ratio for the other user. In the example, user values item ten times more than item , while user values item ten times more than item . The condition could also be interpreted by observing that the product of values for the second item must equal the product of value for the first item. Likewise, if then the second item will attract more votes than the first, and, conversely, if the second item will attract fewer votes than the first item.
Moreover, replacing expression (17) into expression (15), we derive the following expression:
hence
where
Therefore,
Expression (19) provides some interesting information on the relationship between and First, notice that can be any positive number, hence not necessarily less than one.
It follows that is not necessarily a convex combination between, an average of, and In any case, it will always be non-negative.
Then, observe that expression (19) is a decreasing function of ; in particular, tends to as goes to zero, and goes to zero as tends to infinity. For given and this is consistent with the intuition, since goes to zero when goes to zero, which means that the outcome of the first round of voting is by far the most important item for agent . Analogous considerations hold for when goes to infinity.
Additionally, it is also interesting to point out that, for given and , the stake would tend to when is very large as compared to , that is, when user assigns a high value to the outcome of the first voting round. All this implies that agent will set a high as long as one of the two players assigns a high value to the first item, as compared to the other user.
Moreover, is an increasing concave function of, which is equal to for , reaching its maximum value of at .
Furthermore, notice that in the specific case of
then
, which implies that
if
. More generally, based on expression (19), it follows that
holds if
that is, if
To see if and when the inequality in expression (20) can be satisfied, we discuss four possibilities:
- (i)
and then expression (20) is never satisfied;
- (ii)
and , then expression (20) can be satisfied;
- (iii)
and , then expression (20) can be satisfied;
- (iv)
and , then expression (20) is always satisfied.
Points (i)–(iv) suggest how the relative size of and is related to both the users’ values and their budget of votes. For example, according to (i), takes place when is sufficiently smaller than and item is relatively more important for user than for user . Analogous considerations hold for the other three points.
2.5. The General Model of QV
After having gained some early insights into the optimal number of votes, we can now go back to the general formulation of the problem. For a generic success probability
, the optimal allocation of votes with QV can be obtained considering the initial setting of the problem:
Assuming that
and
we find that the optimal
solves the following first-order condition:
Squaring both sides and summing them up over the rounds, we obtain
and therefore
which, without introducing specific assumptions on the shape of
, could not be explicitly determined. Yet, it can be immediately observed that
, with
if and only if
, that is, if, for user
, the marginal expected value of issue
is larger than the marginal expected value of issue
.
If, based on the above considerations, a comparison across votes of the same committee member is immediate and relatively easy to interpret, it is more difficult to compare the number of votes across different users for the same issue.
In some special cases, however, such comparison can be performed with no major problems. Suppose, for example, that the only quantity differing between members and is their total stake, that is, . In this case, it follows immediately that if and only if However, even if the members’ values would differ then, for example, does not necessarily imply for all . Indeed, suppose but that is sufficiently larger than then, it may be
To summarize, when the committee members vote independently of each other, differences in the number of votes allocated to the various rounds depend on three main quantities: the member’s value of the item under voting, the perceived probability of obtaining that value and the total stake of a committee member.
4. Simultaneous versus Sequential Staking
Until now we assumed that users choose, at the beginning of a voting session, both the total number of votes for the entire session as well as the number of votes for each round. More explicitly, at the start of the session, user announces as well as , for each round to which she commits throughout the whole voting session. We also assumed that users choose simultaneously, that is, they communicate to the blockchain platform their choice independently of each other, without having observed how many votes the other users had allocated to the various rounds.
In this section, we analyze some alternative scenarios with sequential staking to discuss whether and how the disclosure of some information could affect the users’ strategy.
In what follows, we consider two cases:
- (1)
at some round, when (at least one) user chooses the number of votes to allocate for that item, they are able to observe the number of votes chosen by the other users for that round.
- (2)
at some round, users are able to observe the votes chosen by the other users in previous rounds and possibly change their plans made at the beginning of the voting session.
(1) We start with the simplest case already mentioned in the Introduction. Suppose there are two users and two voting rounds . Moreover, assume , . That is, the two users have opposite preferences and, furthermore, has a larger budget of votes than. Finally, though we consider the possibility of fractional votes, assume that the outcome of a voting round is valid if at least one user casts one vote in it.
Take user . If when choosing and she does not know then, with QV, a reasonable allocation of votes for her may be since , which is slightly higher in the first round, since she cares more about its outcome. Likewise, since user cares more about the second item, she may decide to cast all of her votes on it, and so , since . As a result, user will have the majority in the first round, while user in the second round. Therefore, even though has a lower overall stake as compared to , she could still guarantee for herself the outcome of the second voting round, i.e., the most desirable for her. So, overall, in the two rounds, both users would secure a value between and units. Indeed, in the first round, , having the majority of votes, would certainly obtain a value of and possibly an additional value of in the second round, if their preferences are aligned with those of user . An analogous reasoning holds for user . In any case, the example shows that the weaker user could be certain to obtain a value of at least . That is, with QV, she could still obtain a sufficiently high value by focusing her votes on the second round.
However, suppose that now knows that has chosen ; then could choose, for example and which is larger than , so that would win both voting rounds and would guarantee for herself the maximum possible value of .
To summarize, even with QV, the sequential staking of the kind discussed in this point can meaningfully affect the outcome of the voting rounds, typically favoring the user with an informational advantage.
(2) In this second case, we consider the following situation. As above, we still assume that users announce at the beginning of a voting session the total number of votes they intend to have as a stake
. However, we now suppose that
is announced simultaneously before each round, rather than at the very beginning of the voting session for all rounds, discussing what difference this would make as compared to the model in
Section 1.
From a conceptual perspective, the main difference with simultaneous announcement at the beginning of the session is given by the following elements. First, except for the first round, after each voting round, the user can observe the outcome of the previous rounds, that is, which of the two alternatives to be chosen prevailed, which, in principle, may provide useful information on how to choose in the following rounds. Moreover, each user could also observe how many votes have been allocated by the other committee members to the previous rounds.
There may be multiple ways of taking account of the above observations to try answering the question, depending upon the user’s goal function. To gain some insights, we study the case of
any power voting,
and
Moreover, we still assume
symmetric agents, as in Proposition 1, and consider the following reasoning.
At the first voting round
, user
solves expression (13) to obtain expression (14), which, for convenience, we report below:
Expression (14) would provide a solution for
as well as an indication, though
not a commitment, for the values of
with
. Hence, assume
is adopted in the first round but then, upon reaching the second round, the user evaluates whether she’s still willing to choose
, as computed by expression (14), or a different number of votes. Suppose that such an alternative number of votes would now be calculated by solving the following problem, which updates expression (13) after the first round:
That is, if
stands for the solution to expression (36), then following the same procedure as in expression (14), we obtain
where
and
. Therefore, still considering a symmetric equilibrium, it is
which implies that
. That is if the user, after the first round, re-calculates the number of votes to choose in the second round and finds, as in expression (36), the same solution, we say that the user is
dynamically consistent at the second round. That is, the number of votes that, in the first round, the user planned to choose for the second round, she will indeed find it convenient to choose upon reaching the second round.
Following a similar reasoning, it can be immediately observed that, upon reaching any voting round, the user will have no incentive to change the number of votes that she planned to use at any round, with .
To summarize, under the assumptions of the model, the simultaneous versus sequential choice of the voting stake will make no difference for the user who, for this reason, we define to be dynamically consistent.
5. A More Detailed Specification of the Users’ Preferences
In
Section 1, we introduced the main fundamentals of the model, assuming that in each round of a voting session users would obtain a positive value if the outcome of the round was the most desirable one, or a zero value otherwise. Admittedly, this might be considered too simplified a representation of the committee members’ preferences, since we did not make it explicit which of the alternatives under voting was preferred by the individuals. Indeed, specifying the alternative that the users prefer may improve our understanding of their behavior when individuals vote under QV.
The following simple example illustrates the point. Consider a session with three voting rounds and three committee members . For each round there is a binary choice to make, which we indicate with . Finally, by we define the value of user in round with preference for alternative and analogously for alternative . As before, we assume that if then , and if then for all users and all rounds. The table below contains a complete description of the users’ preferences over the items under voting.
Some comments are in order.
Table 1 suggests that over the whole voting session, user
is the one with the largest value, equal to
. The total value per user provides an indication on how important the voting session is for them. The “
round value” row provides the total value, for the two alternatives in each round. For example, in round
alternative
has a value of
while
, a value of
which also implies that round
exhibits the highest total value of
. The total value per round provides an indication of the overall importance for the voters of the round under consideration. Moreover, the “Number of users” row summarizes how many users prefer each alternative.
Additionally, the most important item under voting for user is , while for user it is and for it is both and . Finally, the maximum total value that could be obtained in the entire session by the three voters is equal to out of , a little more than a half the overall value of the voting session.
Based on the description of
Table 1, we observe that, from the point of view of the whole “committee”, because of the wide dispersion of preferences and values, regardless of the outcome of the voting rounds, there will be some meaningful “social waste”, in the sense that a value of at least
, namely
of the total value, could not be obtained by anyone in the session.
Given the above preferences, the outcome of each single round of voting will depend on each user’s stake , which is likely to be positively correlated with the total value . Indeed, assume ; in what follows, we discuss what would occur with standard majority voting versus QV.
(i) Standard majority voting. It follows that if they vote independently of each other in the first round, alternative prevails with votes against . In the second round, alternative prevails with votes against . In the third round, prevails again with votes against . Globally, the value achieved in the session is equal to , almost the maximum possible one.
However, there are two points to note here. First, user
, despite having the highest global stake of
for the entire voting session, will be able to obtain only a total value of
, namely just
of their value in the whole voting session. Secondly, user
will obtain
of their value, even though their global stake is the lowest and equal to
.
Table 2 below summarizes all of this.
Majority voting is feared to penalize minorities because in case somebody has more than of the votes, they can always guarantee for themselves the best possible outcome, which sometimes may not coincide with the best possible outcome of minority voters. However, the above example shows that this may not always be the case, since the user with the largest overall value is the one penalized.
Indeed, if the outcome contained in
Table 2 is perceived as unfair/inefficient, we now discuss whether the “any power voting” criterion can somehow improve the situation.
(ii) “
Any power” voting. Suppose now that users have a budget of votes
, as in
Section 2.3, and expression (13), must satisfy constraint
where
In this case, alternative scenarios can take place, depending upon how users would allocate their votes across the rounds.
Start considering and, since , suppose that somewhat naturally, . In this case, it is easy to check that now user will obtain an even lower value than with majority voting, equal to ; user would now increase her total value to , while user would reduce her total value to . If this outcome certainly improves user situation, it further decreases user total value as well as user overall value. Though the unit power seems to be re-balancing the situation for users and , making it more consistent with their overall values, it further deteriorates the situation of . However, as hinted at, the distribution of votes may differ from . For example, if player chooses with the other two players still choosing , a different scenario would be obtained. Now could guarantee for themselves a value of while would obtain an overall value of and a total value of equal to . With that is QV, again several scenarios can take place depending upon the stakes chosen over the three rounds by the users. For example, if users naturally select then it can be immediately noticed that nothing would change with respect to standard majority in terms of voting outcomes. So, if majority voting is perceived as somewhat biased in this case, QV, with the above allocation of votes, would not fix the issue. However, with an alternative distribution of votes, outcomes may change, as it occurred with the unit power .
Finally, as noticed earlier, if the power
becomes large, then
would tend to
and the voting outcome in each round is be determined by how many users will have a positive value for one alternative versus the other alternative. According to
Table 1, the value distribution based on the voting outcomes would again be as in
Table 2, that is, as with majority voting.
To summarize, in the example contained in
Table 1, user
, the one with a lower number of votes, appears to be able to obtain very satisfactory outcomes, both with majority voting as well as with QV. That is, QV does not seem to operate in a special way to “protect” her. A possible intuition for this might be the following. In the three voting rounds, user
is never alone to prefer one of the two alternatives and, moreover, the other user with the same preference has a sufficiently large number of votes. When this occurs, QV would perhaps not be needed for protecting the minorities, since they can obtain their most desirable outcome being supported by other voters. However, when minorities cannot enjoy additional support from other voters, then QV can help them grant for themselves at least some desirable outcome.
To see this, consider the following simple variation of
Table 1.
In
Table 3 below, user
is still the weak one, as in
Table 1 and, moreover, numerically, she is always a minority in the three rounds, as well as in terms of the total value per round. Furthermore, she cares particularly about the third item, which is not the most desirable for the other two voters.
Assuming again
, in
Table 3, user
is certainly a minority and, moreover, in each voting round, she is the only one to prefer her own alternative. Majority voting will certainly prevent her from obtaining any of the desirable results. With unit power
and
, again, user
will not be able to improve her situation. However, if users
and
again choose
but, for example,
then
will be able to guarantee for herself the most desirable outcome in the third round and a total value of
. Likewise, with QV and
for
by posing
then
would be able to secure a total value of
in the third round.