The Blockchain community starts to notice the environmental impact of cryptocurrencies and distributed ledger technologies (DLT). Now, there is a new class of projects which combine sustainability and environment with decentralization, which augments their business utility. In this article, we explore the new wave of eco-blockchains, and why you should get on board quickly.

Electricity consumption and carbon footprint

With the growth in the number of users and transactions, Blockchain systems based on the Proof-of-Work (PoW) mechanism require an increased computing power for miners. That causes increasingly-advanced computations to consume more energy as the network size grows. In turn, PoW-based Blockchains – such as the one of Bitcoin – have over time become environmentally unsustainable, because of their high energy consumption. Proof-of-Stake consensus model – e.g. in Ethereum – requires slightly less energy but does not eliminate the problem of limited scalability.

Energy consumption

BTC alone represents 43% of the overall crypto traffic, which makes it the most popular cryptocurrency. The Bitcoin network has the greatest carbon footprint due to its energy consumption. According to the Bitcoin Energy Consumption Index, it’s estimated that Bitcoin mining requires 178 TWh of electrical power – roughly the same as the annual consumption of energy in Poland.

Because of the environmental impact of mining, cryptocurrencies are criticized and compared to centralized financial tools. For example, one BTC creating a new block requires 1779 kWh of power, while 100,000 transactions operated by the payment card provider VISA, consume 189 kWh only. In one transaction, Bitcoin uses as much electricity as an average American household in 67 days.

Eco blockchains - more sustainable future

Taking into account all the environmental considerations, the new generation of sustainable Blockchains has emerged in response to skyrocketing consumption of miners in conventional cryptocurrencies. Apart from ethical arguments, the reason for their rising popularity is scalability. With the rising prices of cryptocurrencies, miners need to process a greater volume of transactions; especially in 2021, the problem of rising electricity prices and power consumption became a pressing issue, making eco-friendly Blockchains not only an environmentally-sound proposition but also a very convincing use case in business.

1. Chia - energy-efficient alternative

The Chia coin, powered by the Blockchain called Chia Network, skyrocketed in mid-2021 after its public mainnet launch. The Chia founder, Brian Cohen, is the author of popular software and protocol, BitTorrent. The platform was valuated at $500 million in a recent investment round. The Chia Network is currently the fastest-growing green Blockchain. It is also a smart transaction platform that allows users to take advantage of available hard drive space. Because Chia is also a smart contract platform, there is a new wave of further innovative projects released on the Chia Network that take advantage of carbon-neutral, scalable solutions of the space-based consensus mechanism.

The Chia solution uses much less electricity compared to cryptocurrencies powered by PoW or the PoS consensus mechanism and allows more people to start mining at a lower cost. To become a Chia miner, one has to simply devote their disc space or use cloud computing platforms such as Amazon Web Services. Since Chia's launch in March 2021, Chia's computer memory usage has grown exponentially. While in mid-May 2021 it was about half a million terabytes of memory, in October this figure multiplied ten times.

Unlike previous cryptocurrencies, the Chia coin is powered by a Blockchain using the Proof-of-Space-and-Time mechanism. As a result, Chia mining uses neither GPU nor CPU architecture to enable the exchange of data and value, but computer memory. Miners’ hard drive or SSD space powering the Chia Blockchain is connected to the decentralized network where storing a certain amount of data over a certain amount of time is rewarded in XCH, Chia’s token.

Chia farming is accessible, with neither specialized equipment needed nor massive amounts of power. This makes it not The network’s blockchain transaction platform can be downloaded at chia.net. Users can decide to dedicate a portion of uncommitted hard drive space to the network and receive XCH in exchange, without significantly affecting computer performance or requiring vastly more energy.

2. SolarCoin

Unlike Chia, which is a brand-new Blockchain and consensus mechanism, SolarCoin exploits the simple idea of smart contracts. It follows the logic of all other cryptocurrencies, but the key difference is that the platform design aims to incentivize real-world environmental activity: verifiably produced solar energy. The smart contract distributes 1 SolarCoin (SLR) for every MWh (megawatt hour) generated from solar panel technology.

SolarCoin relies on two forms of Proof-of-Work (PoW) protocol. The first is the traditional cryptographic PoW associated with the most conventional cryptocurrencies (e.g. Bitcoin). The second-layer PoW is a verified mechanism that indicates whether the said 1 MWh of power was proved to be produced from solar energy. Then the smart contract distributes SolarCoins using these two PoWs as a means of rewarding green electricity generation.

3. IOTA

As a great add-on to IOTA’s tech proposition, its environmentally-oriented approach is achieved by eliminating miners, since they are the cause of environmental problems of cryptocurrencies. IOTA uses an alternative to conventional Blockchain called the ‘Tangle’. Instead of mining, the network is maintained by smaller devices and uses calculations that require less power and thus consume less energy per transaction (0.00011 kWh per transaction), making it the most environmentally sustainable among the leading cryptocurrencies.

The whole crypto community is getting green – so should you!

There are visible signs that the crypto developers are increasingly aware and active to find new ways of offering all the benefits of cryptocurrencies, with none of the unsustainable and environment-harming drawbacks.

Leading Blockchain firms and corporations signed the Crypto Climate Accord. Its objective is to decarbonize the crypto industry and make it a net-zero greenhouse gas emitter by 2040. It was signed by such important names as Ripple, Consensys, Polygon – and among corporate giants: KPMG and NortonLifeLock.

Whether environmentally friendly by design or business choice, the crypto industry has very convincing arguments to ‘go green’. In the current form, the most popular cryptocurrencies like BTC have been heavily criticised for their unsustainability. Decentralization efforts cannot be sustained if the environmental costs of powering transactions keep rising. Hence, the rise of a new wave of green Blockchains and green cryptocurrencies a clear call to action for several stakeholders.

Given the early stage of development, environment-neutral cryptocurrencies and decentralized protocols are a great space for entrepreneurs to get involved. They can develop their own solutions based on sustainable Blockchains. Beyond optimizations in consensus mechanisms and DLT architectures, there are some of the most exciting business cases, such as green NFTs, exchanges and storage platforms.

If you want to know how to build your projects based on eco-Blockchains, contact our experts who will be happy to give you a free consultation.

Applying Game Theory in Token Design

Kajetan Olas

16 Apr 2024

Blockchain technology allows for aligning incentives among network participants by rewarding desired behaviors with tokens.
But there is more to it than simply fostering cooperation. Game theory allows for designing incentive-machines that can't be turned-off and resemble artificial life.

Emergent Optimization

Game theory provides a robust framework for analyzing strategic interactions with mathematical models, which is particularly useful in blockchain environments where multiple stakeholders interact within a set of predefined rules. By applying this framework to token systems, developers can design systems that influence the emergent behaviors of network participants. This ensures the stability and effectiveness of the ecosystem.

Bonding Curves

Bonding curves are tool used in token design to manage the relationship between price and token supply predictably. Essentially, a bonding curve is a mathematical curve that defines the price of a token based on its supply. The more tokens that are bought, the higher the price climbs, and vice versa. This model incentivizes early adoption and can help stabilize a token’s economy over time.

For example, a bonding curve could be designed to slow down price increases after certain milestones are reached, thus preventing speculative bubbles and encouraging steadier, more organic growth.

The Case of Bitcoin

Bitcoin’s design incorporates game theory, most notably through its consensus mechanism of proof-of-work (PoW). Its reward function optimizes for security (hashrate) by optimizing for maximum electricity usage. Therefore, optimizing for its legitimate goal of being secure also inadvertently optimizes for corrupting natural environment. Another emergent outcome of PoW is the creation of mining pools, that increase centralization.

The Paperclip Maximizer and the dangers of blockchain economy

What’s the connection between AI from the story and decentralized economies? Blockchain-based incentive systems also can’t be turned off. This means that if we design an incentive system that optimizes towards a wrong objective, we might be unable to change it. Bitcoin critics argue that the PoW consensus mechanism optimizes toward destroying planet Earth.

Layer 2 Solutions

Layer 2 solutions are built on the understanding that the security provided by this core kernel of certainty can be used as an anchor. This anchor then supports additional economic mechanisms that operate off the blockchain, extending the utility of public blockchains like Ethereum. These mechanisms include state channels, sidechains, or plasma, each offering a way to conduct transactions off-chain while still being able to refer back to the anchored security of the main chain if necessary.

Conceptual Example of State Channels

State channels allow participants to perform numerous transactions off-chain, with the blockchain serving as a backstop in case of disputes or malfeasance.

Consider two players, Alice and Bob, who want to play a game of tic-tac-toe with stakes in Ethereum. The naive approach would be to interact directly with a smart contract for every move, which would be slow and costly. Instead, they can use a state channel for their game.

Opening the Channel: They start by deploying a "Judge" smart contract on Ethereum, which holds the 1 ETH wager. The contract knows the rules of the game and the identities of the players.
Playing the Game: Alice and Bob play the game off-chain by signing each move as transactions, which are exchanged directly between them but not broadcast to the blockchain. Each transaction includes a nonce to ensure moves are kept in order.
Closing the Channel: When the game ends, the final state (i.e., the sequence of moves) is sent to the Judge contract, which pays out the wager to the winner after confirming both parties agree on the outcome.

A threat stronger than the execution

If Bob tries to cheat by submitting an old state where he was winning, Alice can challenge this during a dispute period by submitting a newer signed state. The Judge contract can verify the authenticity and order of these states due to the nonces, ensuring the integrity of the game. Thus, the mere threat of execution (submitting the state to the blockchain and having the fraud exposed) secures the off-chain interactions.

Game Theory in Practice

Understanding the application of game theory within blockchain and token ecosystems requires a structured approach to analyzing how stakeholders interact, defining possible actions they can take, and understanding the causal relationships within the system. This structured analysis helps in creating effective strategies that ensure the system operates as intended.

Stakeholder Analysis

Identifying Stakeholders

The first step in applying game theory effectively is identifying all relevant stakeholders within the ecosystem. This includes direct participants such as users, miners, and developers but also external entities like regulators, potential attackers, and partner organizations. Understanding who the stakeholders are and what their interests and capabilities are is crucial for predicting how they might interact within the system.

_{Stakeholders in blockchain development for systems engineering}

Assessing Incentives and Capabilities

Each stakeholder has different motivations and resources at their disposal. For instance, miners are motivated by block rewards and transaction fees, while users seek fast, secure, and cheap transactions. Clearly defining these incentives helps in predicting how changes to the system’s rules and parameters might influence their behaviors.

Defining Action Space

Possible Actions

The action space encompasses all possible decisions or strategies stakeholders can employ in response to the ecosystem's dynamics. For example, a miner might choose to increase computational power, a user might decide to hold or sell tokens, and a developer might propose changes to the protocol.

Constraints and Opportunities

Understanding the constraints (such as economic costs, technological limitations, and regulatory frameworks) and opportunities (such as new technological advancements or changes in market demand) within which these actions take place is vital. This helps in modeling potential strategies stakeholders might adopt.

Causal Relationships Diagram

Mapping Interactions

Creating a diagram that represents the causal relationships between different actions and outcomes within the ecosystem can illuminate how complex interactions unfold. This diagram helps in identifying which variables influence others and how they do so, making it easier to predict the outcomes of certain actions.

Analyzing Impact

By examining the causal relationships, developers and system designers can identify critical leverage points where small changes could have significant impacts. This analysis is crucial for enhancing system stability and ensuring its efficiency.

Feedback Loops

Understanding feedback loops within a blockchain ecosystem is critical as they can significantly amplify or mitigate the effects of changes within the system. These loops can reinforce or counteract trends, leading to rapid growth or decline.

Reinforcing Loops

Reinforcing loops are feedback mechanisms that amplify the effects of a trend or action. For example, increased adoption of a blockchain platform can lead to more developers creating applications on it, which in turn leads to further adoption. This positive feedback loop can drive rapid growth and success.

Death Spiral

Conversely, a death spiral is a type of reinforcing loop that leads to negative outcomes. An example might be the increasing cost of transaction fees leading to decreased usage of the blockchain, which reduces the incentive for miners to secure the network, further decreasing system performance and user adoption. Identifying potential death spirals early is crucial for maintaining the ecosystem's health.

Conclusion

The fundamental advantage of token-based systems is being able to reward desired behavior. To capitalize on that possibility, token engineers put careful attention into optimization and designing incentives for long-term growth.

FAQ

What does game theory contribute to blockchain token design?
- Game theory optimizes blockchain ecosystems by structuring incentives that reward desired behavior.
How do bonding curves apply game theory to improve token economics?
- Bonding curves set token pricing that adjusts with supply changes, strategically incentivizing early purchases and penalizing speculation.
What benefits do Layer 2 solutions provide in the context of game theory?
- Layer 2 solutions leverage game theory, by creating systems where the threat of reporting fraudulent behavior ensures honest participation.

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Token Engineering Process

Kajetan Olas

13 Apr 2024

Token Engineering is an emerging field that addresses the systematic design and engineering of blockchain-based tokens. It applies rigorous mathematical methods from the Complex Systems Engineering discipline to tokenomics design.

In this article, we will walk through the Token Engineering Process and break it down into three key stages. Discovery Phase, Design Phase, and Deployment Phase.

Table of Contents

Discovery Phase of Token Engineering Process
Design Phase of Token Engineering Process
- Objective Function
Deployment Phase of Token Engineering Process
Time Duration
Required Skills for Token Engineering
Summary
FAQ

Discovery Phase of Token Engineering Process

The first stage of the token engineering process is the Discovery Phase. It focuses on constructing high-level business plans, defining objectives, and identifying problems to be solved. That phase is also the time when token engineers first define key stakeholders in the project.

Defining the Problem

This may seem counterintuitive. Why would we start with the problem when designing tokenomics? Shouldn’t we start with more down-to-earth matters like token supply? The answer is No. Tokens are a medium for creating and exchanging value within a project’s ecosystem. Since crypto projects draw their value from solving problems that can’t be solved through TradFi mechanisms, their tokenomics should reflect that.

The industry standard, developed by McKinsey & Co. and adapted to token engineering purposes by Outlier Ventures, is structuring the problem through a logic tree, following MECE.
MECE stands for Mutually Exclusive, Collectively Exhaustive. Mutually Exclusive means that problems in the tree should not overlap. Collectively Exhaustive means that the tree should cover all issues.

In practice, the “Problem” should be replaced by a whole problem statement worksheet. The same will hold for some of the boxes.
A commonly used tool for designing these kinds of diagrams is the Miro whiteboard.

Identifying Stakeholders and Value Flows in Token Engineering

This part is about identifying all relevant actors in the ecosystem and how value flows between them. To illustrate what we mean let’s consider an example of NFT marketplace. In its case, relevant actors might be sellers, buyers, NFT creators, and a marketplace owner. Possible value flow when conducting a transaction might be: buyer gets rid of his tokens, seller gets some of them, marketplace owner gets some of them as fees, and NFT creators get some of them as royalties.

Incentive Mechanisms Canvas

The last part of what we consider to be in the Discovery Phase is filling the Incentive Mechanisms Canvas. After successfully identifying value flows in the previous stage, token engineers search for frictions to desired behaviors and point out the undesired behaviors. For example, friction to activity on an NFT marketplace might be respecting royalty fees by marketplace owners since it reduces value flowing to the seller.

_{source: https://www.canva.com/design/DAFDTNKsIJs/8Ky9EoJJI7p98qKLIu2XNw/view#7}

Design Phase of Token Engineering Process

The second stage of the Token Engineering Process is the Design Phase in which you make use of high-level descriptions from the previous step to come up with a specific design of the project. This will include everything that can be usually found in crypto whitepapers (e.g. governance mechanisms, incentive mechanisms, token supply, etc). After finishing the design, token engineers should represent the whole value flow and transactional logic on detailed visual diagrams. These diagrams will be a basis for creating mathematical models in the Deployment Phase.

Token Engineering Artonomous Design Diagram — _{Artonomous design diagram, source: Artonomous GitHub}

Objective Function

Every crypto project has some objective. The objective can consist of many goals, such as decentralization or token price. The objective function is a mathematical function assigning weights to different factors that influence the main objective in the order of their importance. This function will be a reference for machine learning algorithms in the next steps. They will try to find quantitative parameters (e.g. network fees) that maximize the output of this function.
Modified Metcalfe’s Law can serve as an inspiration during that step. It’s a framework for valuing crypto projects, but we believe that after adjustments it can also be used in this context.

Deployment Phase of Token Engineering Process

The Deployment Phase is final, but also the most demanding step in the process. It involves the implementation of machine learning algorithms that test our assumptions and optimize quantitative parameters. Token Engineering draws from Nassim Taleb’s concept of Antifragility and extensively uses feedback loops to make a system that gains from arising shocks.

Agent-based Modelling

In agent-based modeling, we describe a set of behaviors and goals displayed by each agent participating in the system (this is why previous steps focused so much on describing stakeholders). Each agent is controlled by an autonomous AI and continuously optimizes his strategy. He learns from his experience and can mimic the behavior of other agents if he finds it effective (Reinforced Learning). This approach allows for mimicking real users, who adapt their strategies with time. An example adaptive agent would be a cryptocurrency trader, who changes his trading strategy in response to experiencing a loss of money.

Monte Carlo Simulations

Token Engineers use the Monte Carlo method to simulate the consequences of various possible interactions while taking into account the probability of their occurrence. By running a large number of simulations it’s possible to stress-test the project in multiple scenarios and identify emergent risks.

Testnet Deployment

If possible, it's highly beneficial for projects to extend the testing phase even further by letting real users use the network. Idea is the same as in agent-based testing - continuous optimization based on provided metrics. Furthermore, in case the project considers airdropping its tokens, giving them to early users is a great strategy. Even though part of the activity will be disingenuine and airdrop-oriented, such strategy still works better than most.

Time Duration

Token engineering process may take from as little as 2 weeks to as much as 5 months. It depends on the project category (Layer 1 protocol will require more time, than a simple DApp), and security requirements. For example, a bank issuing its digital token will have a very low risk tolerance.

Required Skills for Token Engineering

Token engineering is a multidisciplinary field and requires a great amount of specialized knowledge. Key knowledge areas are:

Systems Engineering
Machine Learning
Market Research
Capital Markets
Current trends in Web3
Blockchain Engineering
Statistics

Summary

The token engineering process consists of 3 steps: Discovery Phase, Design Phase, and Deployment Phase. It’s utilized mostly by established blockchain projects, and financial institutions like the International Monetary Fund. Even though it’s a very resource-consuming process, we believe it’s worth it. Projects that went through scrupulous design and testing before launch are much more likely to receive VC funding and be in the 10% of crypto projects that survive the bear market. Going through that process also has a symbolic meaning - it shows that the project is long-term oriented.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to contact@nextrope.com. Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.

FAQ

What does token engineering process look like?

Token engineering process is conducted in a 3-step methodical fashion. This includes Discovery Phase, Design Phase, and Deployment Phase. Each of these stages should be tailored to the specific needs of a project.

Is token engineering meant only for big projects?

We recommend that even small projects go through a simplified design and optimization process. This increases community's trust and makes sure that the tokenomics doesn't have any obvious flaws.

How long does the token engineering process take?

It depends on the project and may range from 2 weeks to 5 months.