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Distributed resource governance on a blockchain

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This research proposes a novel method for ensuring fair governance of a common resource recorded on a blockchain. It features a self-governing system of stakeholders, managing resources by taking on the roles of auditors and claimants in place of having an overseeing bureaucracy with its accompanying overhead costs. While self-governing can be subject to fraud and collusion, in the proposed governance system, anonymity, a staple of blockchain transactions, is utilized to mitigate these negative effects. This is done by assigning random anonymous auditors to resource claimants. Cheating, along with improper auditing, will result in penalties for both auditor and claimant. Improper auditing consists not only of allowing unlawful resource use, but also denying lawful use. The proof of concept system is a distributed application running on a Hyperledger Fabric blockchain. All activities are recorded as immutable public transactions on the blockchain. A simulation and a blockchain application to support further investigations are presented.
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Distributed resource governance on a blockchain
1
Distributed resource governance on a blockchain
Thomas E. Portegys, portegys@gmail.com , ORCID 0000-0003-0087-6363
Dialectek, DeKalb, Illinois USA
ABSTRACT
This research proposes a novel method for ensuring fair governance of a common resource recorded on a blockchain. It features
a self-governing system of stakeholders, managing resources by taking on the roles of auditors and claimants in place of having
an overseeing bureaucracy with its accompanying overhead costs. While self-governing can be subject to fraud and collusion,
in the proposed governance system, anonymity, a staple of blockchain transactions, is utilized to mitigate these negative effects.
This is done by assigning random anonymous auditors to resource claimants. Cheating, along with improper auditing, will
result in penalties for both auditor and claimant. Improper auditing consists not only of allowing unlawful resource use, but
also denying lawful use. The proof of concept system is a distributed application running on a Hyperledger Fabric blockchain.
All activities are recorded as immutable public transactions on the blockchain. A simulation and a blockchain application to
support further investigations are presented.
Keywords
Resource governance, blockchain, distributed application, anonymity, Hyperledger.
INTRODUCTION
Technology has densely connected people. While we are awash in information, most organizations retain cen tralized control
and authority structures that concentrate power hierarchically. This reflects the divide-and-conquer strategy, with expertise and
skilled specialists occupying niches where people collaborate in close contact, featuring high bandwidth, low latency
communication.
While a historically successful scheme, drawbacks of a hierarchical organization include opacity to stakeholders not residing
in a particular walled garden, and often with concomitant inefficiencies, obsolescences, and malfeasance that take root in more
entrenched bureaucracies. People tend to become resigned to this eventuality, demonstrated by complacently paying taxes,
premiums and dues, dutifully voting and showing up to board, town, and union meetings, all the while ceding authority to duly
appointed representatives. That people are often unable to identify their elected representatives, for example, testifies to the
enervating and disengaging effect of having information and responsibility without direct authority and involvement.
While acknowledging the value of full-time experts and specialists, there is also value in allowing organizational stakeholders
to exercise some authority in formulating policies, plans and actions from the perspective of those affected by these things
(Phillips, et. al., 2009). The customary problem with this approach is that, although stakeholders are motivated for an
organization to succeed, they are also outsiders that are neither sufficiently knowledgeable nor available to perform decision-
making roles. Technology offers a means to address this issue. Many complex organizations have already moved in the
direction of distributed control with great success -- open source teams are an example of this. The key notion is not just offering
openness, but also real authority; without authority interest will wane for many. The advantage is more eyes and hands and less
expense. The risk is allowing less knowledgeable people to have a say, and whether they will defer to experts when it is
appropriate.
Frequently, by choice or circumstance, the resources of a group are cast into a common pool. An example of a choice would
be to pay a periodic fee for insurance to lessen the financial severity of a car accident. A natural resource such a river is an
example of a circumstantial shared pool, the use of which is sometimes framed as a commons dilemma (Hardin, 1968), in which
the short-term selfish interests of individuals are opposed to long-term group interests. A typical way to ensure proper resource
usage is through a regulatory organization. Such organizations commonly incur substantial costs to support a bureaucracy and
facilities to administrate rules and laws that govern resource usage.
A type of contract is proposed that is a more economical means of achieving fair resource usage by relying on the stakeholders
bound to the contract to enforce the rules, rather than relying on a special organization to do so. In other words, it is believed
that a flattened distributed administration can operate in a more cost-effective way. It is known that self-enforcement (“the
honor system”) and mutual enforcement can facilitate cheating and abuse through deal-making, conspiracy and secretive
behavior. In the proposed contract, anonymity, a staple of blockchain transactions, is employed to reduce side channels used
Distributed resource governance on a blockchain
2
for collaborative cheating thus fostering mutually beneficial behavior. This is done by assigning random anonymous auditors
to a resource claimant. Cheating and abuse, along with improper auditing, result in penalties. Improper auditing consists not
only of allowing unlawful resource use, but also denying lawful use.
Anonymous online behavior is well-known to have negative consequences, especially when the identities of those involved in
behaviors such as trolling and cyberbullying are hidden from view but the victims are known (Herring et al., 2002; Tokunaga,
2010). However, when anonymity is used equitably, it has been found to reduce the negative effects of power and status
differences in decision-making groups (Kiesler and Sproull, 1992; Dubrovsky et al., 1991). Of special relevance to this project,
Wright and Stepney (2008) note that anonymity is widely-used in situations where knowledge of individual users could lead
to favoritism, discrimination or collusion (e.g., voting, the marking of exam papers, review of funding applications and
academic peer-review).
Blockchain is an ideal candidate for recording resource transactions, since it inherently supports anonymous, distributed,
immutable, and public transactions (The Economist, 2015). A blockchain is a distributed database or ledger that is shared
among the nodes of a computer network, maintaining a secure and decentralized record of transactions. It guarantees the fidelity
and security of data and generates trust without the need for a trusted third party. No individual stakeholder controls the
blockchain, and everyone can see the outcome of every transaction. Blockchains also feature smart contracts, which is computer
code that resides and runs in the blockchain and provides functional application-specific processing of transactions
(Governatori et al., 2018)
Other features on the technological landscape that facilitate the proposed contract are the ubiquity and ever-lower latency of
online interactions, allowing prompt auditing activity to take place, and the deep reach and rich fidelity of digital information
sources, allowing intensive remote verification of resource claims.
In the following sections, a preliminary simulation and a Hyperledger Fabric blockchain (2022) application to support further
investigations are presented.
SIMULATION
A simulation using autonomous software agents as stakeholders was done to better understand the problem space and
plausibility of the concepts. The simulation compared a regulatory agency system with a proposed distributed one. Stakeholders
are enrolled in both systems for comparison. Stakeholders share a pool of commons resources that they can make claims on. In
the regulatory agency system, stakeholders pay a fee to administrate claims, ensuring that no cheating occurs. In the distributed
governance system, cheating can happen, dampened by the presence of claim auditors.
A run consists of a number of rounds. In each round, claims are dispersed to a random set of stakeholders. A claim represents
an amount that can be lawfully withdrawn from the commons resources. A granted claim increments the resources of the
claimant, and fractionally reduces the resources of all the stakeholders. In the regulatory agency system, all claims are lawful
and granted, since it is assumed that cheating will be caught by the administration agency. In the distributed governance system,
lawful claims are also granted; however, a claim also represents an opportunity to cheat by withdrawing an unlawful amount
of resources. Stakeholders have a parameterized tendency to cheat. If unsuccessful, the claimant is penalized by losing his share
of commons resources. After each round, stakeholder financial statuses are tabulated.
In the distributed system an auditor is assigned to each claim. An auditor probabilistically decides to allow or deny both lawful
and unlawful claims. The resolution of the claim is decided by the consensus of the auditors. If the distributed system works
sufficiently well, due to its low overhead, it will tend to pay off better than the regulatory system. However, if cheating is
excessively granted, the regulatory system will tend to pay off better for stakeholders other than the successful cheaters. At the
end of the run, the performance of each system is measured by the relative number of stakeholders that find it more financially
beneficial.
Distributed resource governance on a blockchain
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Figure 1 Regulatory Agency vs. Distributed System preference ratio with one auditor per claim
Audit error probability
Cheat attempt probability
0.0
0.1
0.2
0.3
0.4
0.0
0.02
0.05
0.07
0.10
0.0
0.04
0.04
0.06
0.09
0.0
0.09
0.07
0.07
0.13
0.0
0.19
0.16
0.19
0.19
0.0
0.28
0.31
0.30
0.34
Table 1 - Regulatory Agency vs. Distributed System preference with one auditor per claim
Figure 1 and Table 1 show the effect of auditing claims on preference for the regulatory agency vs. the distributed system.
When there is no cheating the distributed system is preferred exclusively. As cheating increases, but with errorle ss auditing to
catch it, the distributed system is strongly preferred. In this situation, it is penalized cheaters that suffer in the Distributed
system and thus choose the regulatory agency system. It is only under the conditions of widespread cheating and error-prone
auditing, resulting in widespread losses caused by successful cheating, that the regulatory agency system stakes a significant
preference.
The main conclusion to be drawn from the simulation is that the presence of claim auditors, even mistake-prone ones, has a
powerful dampening effect on the success rate of cheaters, resulting in a significant stakeholder allegiance to the audited
distributed system.
BLOCKCHAIN APPLICATION
An application in the form of an online game can be used to test the performance of a contract using test subjects as stakeholders.
Rules for Game
1. Initially, stakeholders each contribute an amount into a resource pool called a commons. This amount is denoted as
 for stakeholder i. The commons thus contains  = ∑. is always the same value for all stakeholders,
signifying an equal ownership of . In addition, each stakeholder has a personal account denoted by . This
amount can vary in value.
2. A resource entitlement for claimant i () is generated from a Gaussian probability distribution that represents an
abstraction of the evidence supporting a resource claim. This is essentially a Baysian prior probability. For example,
an entitlement for a pair of shoes would typically run in the tens of dollars, although fringe cases can run down into a
few dollars and up into the hundreds or even thousands of dollars. In a real-life scenario, the probability distribution
is replaced by substantiations for a resource claim sent to claim auditors.  is decremented from , signifying a
loss of resources for the stakeholder.
0
0.3
0
0.1
0.2
0.3
0.4
00.1 0.2 0.3 0.4
Audit error
probability
Regulatory
agency
preference
Cheat attempt probability
Regulatory vs. Distributed Preference
0.3-0.4 0.2-0.3 0.1-0.2 0-0.1
Distributed resource governance on a blockchain
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3. The stakeholder, assuming the role of claimant, uses  and to select a claim amount () that will pass auditing
and satisfy . An amount less than the entitlement might tend to have a better audit outcome, while a greater amount
signifies "cheating" that grants resources exceeding the entitlement.  is selected before any auditors are assigned
to the claim and cannot be modified later.  is not revealed to the auditors as part of the claim.
4. The claim is then assigned a number of random auditors taken from a pool of resource stakeholders. In order to
discourage collusion, the claimant and auditors remain anonymous to each other. The number of auditors is also
unknown to all. An auditor is allowed to anonymously communicate with the claimant to provide further claim
information.
5. An auditor uses representing the claim evidence to determine a grant amount (). To prevent collaborative
cheating,  cannot be greater than . The mean of all the auditor grant amounts (
) is the amount of resources
granted to the claimant ( = 
). is then incremented by , signifying a resource compensation.
6. To promote claimant honesty, if  , a penalty 󰇛󰇜 is subtracted from the grant that is a function of the
difference between the claim and the grant 󰇛 = 󰇛 󰇜󰇜. This will steer claimants away from making
excessive claims.  is then added to the commons.
7. To promote auditor honesty, each auditor is penalized󰇛󰇜 in proportion to the difference between the auditor's
grant and the claim grant󰇛 = 󰇛 󰇜󰇜 This is meant to discourage both unfair denial and illegitimate
generosity to claims. Thus an auditor who colludes with a claimant to grant a large claim runs the risk of penalization
by deviating from the grant mean.  is then added to the commons.
8. There are three ways to score the game:
a. As in the Phase 1 simulation, a measurement of the preference ratio for a competing regulatory vs. the
distributed system can be used as a score. The regulatory agency system exacts a processing fee from all
stakeholders per claim. At the end of a session, each stakeholder will prefer the system that is more financially
beneficial.
b. The standard deviation of the stakeholder resources, = + , can be used as a score. A perfect score
is zero, indicating that every entitlement/claim/grant triplet was for the same amount and there were thus no
penalties. Cheating, denial of resources or penalties will likely skew the resources of the stakeholders; for
example, successful cheaters will have relatively more resources than other stakeholders.
c. A measurement of the depletion of the commons resources. This would be computable from the initial and
final commons resources and the total entitlements. If the final commons amount is less than initial amount
less the total entitlements, then the commons has been excessively depleted.
9. Optionally, since auditor effort has an expense, the resource pool will be reduced for the time spent by auditors to
process claims. This will curtail the excessive use of auditors.
Expected Results
It might be expected that the best long-term strategy would be to grant the probability distribution midpoint amount for every
claim. However, in the short term, this will result in grants that statistically vary from the entitled amounts. Stakeholders trade
transactional privacy in return for the possibility of lower costs. Having stakeholders alternately take on the roles of claimant
and auditor encourages cooperative tit for tat behavior (Axelrod, 1984).
Independent Variables
Possible independent variables include:
1. Competing regulatory system claim processing fee.
2. Commons resource amount.
3. Number of stakeholders.
4. Average number of auditors.
Distributed resource governance on a blockchain
5
5. Penalty functions.
Implementation
The implementation consists of a Hyperledger Fabric blockchain application that allows a host and players to participate in the
game. The client interfaces for the game have been designed for the stakeholder roles of claimant and auditor. The Hyperledger
Fabric code may be found at https://github.com/dialectek/ConformativeChain. A previous incarnation of the app resides on the
Google App Engine at http://conformativegame.appspot.com (Portegys and Wolf, 2011). The blockchain instantiation is a
direct port of the App Engine functionality, thus contains a host” client that lets a user orchestrate transactions. The hos t
algorithms will be incorporated into the blockchain code in a future release to complete the smart contract.
Figure 2 shows the state of player “Alice” as a claimant at the conclusion of a successful claim transaction. For anonymity and
authentication purposes, the player name could also be a public key provided to a user. Alice is entitled to a claim of 13.43
from the common resources. This value was probabilistically sampled from the shown distribution which represents an
abstraction of some event incurring an expense that justifies a claim. This obviously means that a particular claim could appear
excessive or too low to auditors. In this case the auditor has granted the entire claim. The claimant and auditors can option ally
chat each other before the auditors determine a grant amount. A penalty is then calculated from the difference of the claim and
the grant amount, which in this case is 0.
Figure 2 Claimant transaction completion.
Figure 3 shows the claim transaction completion of the auditor, “Bob”, who has granted the entire claim. Since Bob was the
only auditor for this claim, the consensus grant is equal to Bob’s grant, and thus there is no penalty for Bob.
Distributed resource governance on a blockchain
6
Figure 3 Auditor transaction completion.
Figure 4 shows that Alice has received 13.43 in resources from the common resource pool, and equal deductions have been
made from each player’s common resources to fund the grant.
Figure 4 Claimant resource acquisition.
Distributed resource governance on a blockchain
7
CONCLUSION
The hope with this research is to demonstrate a workable method for governing a common resource that uses anonymity in the
role of auditors drawn from a pool of stakeholders. A preliminary simulation points to the plausibility of the method, chiefly
by exhibiting a dampening effect that auditing has on cheating. A more thorough test platform is laid out with the blockcha in
application.
On a larger scale, this study aims to raise awareness of how organizations might leverage a technological landscape that is
connecting people into ever denser communication webs. Blockchain fits in as a means of spanning proprietary and localized
databases with a shared ledger of public transactions and operations.
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Distributed Resource Governance Using Asymmetric Anonymity
  • T Portegys
  • J R Wolf
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