Computecoin Network: The Infrastructure of Web 3.0 and The Metaverse
Abstract
Web 3.0, an evolution of Web 2.0, refers to decentralized applications (dAPP) that run on the blockchain. These are the applications that allow anyone to participate with their personal data well protected and controlled by themselves. However, there are quite a few challenges in the development of Web 3.0 such as accessibility (i.e., less accessible to most users as that in modern web browsers) and scalability (i.e., high cost and long learning curve for using decentralized infrastructure).
For instance, although non-fungible token (NFT) is stored on blockchain, the content of most NFTs is still stored in centralized clouds such as AWS or google clouds. This puts a high risk on user’s NFT assets, contradicting the nature of Web 3.0.
The metaverse, first proposed by Neal Stephenson in 1992, refers to an infinitely vast patchwork of persistent virtual worlds in which people can freely travel, socialize and work. However, metaverse applications and platforms such as Fortnite and Roblox face an enormous challenge: their growth is limited by a finite supply of low-cost and instantaneous computing power from centralized clouds.
In summary, building the next-generation applications on the current centralized infrastructure (built since 1990s) has become the bottleneck on the critical path towards our dreamed world.
We have initiated this project, the Computecoin network along with its native token CCN, to resolve this issue. Our objective is to build the next-generation infrastructure for all-purpose applications on Web3 and the metaverse. In other words, we aims to do for web 3.0 and the metaverse what centralized cloud providers did for Web 2.0.
The basic idea of our system is to first aggregate decentralized clouds such as Filecoin and data centers around the world (rather than build new infrastructure as AWS did 20 years ago) and then offload computation to a proximity network of the nearby aggregated decentralized clouds to empower end users’ data processing tasks such as AR/VR 3D rendering and real-time data storage in a low-cost and instantaneous manner.
Computecoin network comprises two layers: PEKKA and the metaverse computing protocol (MCP). PEKKA is an aggregator and scheduler that seamlessly integrates decentralized clouds and dynamically offloads computation to a proximity network. PEKKA’s capabilities include deploying web3 and metaverse applications to decentralized clouds in a matter of minutes, and providing a unified API for easy data storage and retrieval from any decentralized cloud, like Filecoin or Crust.
The MCP is a layer-0.5/layer-1 blockchain featuring an original consensus algorithm, proof of honesty (PoH), which guarantees that the results of outsourced computation in the decentralized cloud network are authentic. In other words, PoH establishes trust in computation tasks outsourced to trustless decentralized clouds, building the foundation for web 3.0 and the metaverse ecosystem.
I. INTRODUCTION
It is widely agreed that Web 3.0 is the key to actualizing a more decentralized and interactive experience in the metaverse. As a result, we usually view Web 3.0 and related technologies as the building blocks for the metaverse. Therefore, in what follows, we focus our discussion on the metaverse, the ultimate goal that computecoin targets.
A. Introduction to metaverse
Imagine every activity and experience in your daily life taking place within arm’s reach of each other. Imagine seamless transit between each space, each node, you inhabit and the people and things you interact within them. This vision of pure connectivity serves as the beating heart of the metaverse.
The metaverse, as its name suggests, refers to an infinitely vast patchwork of persistent virtual worlds between which people can freely travel. Neal Stephenson is often credited with laying out the first description of the metaverse in his seminal 1992 science fiction novel Snow Crash. Since then, dozens of projects — everything from Fortnite and Second Life to CryptoKitties and Decentraland — have nudged humanity closer to the metaverse.
When it does take shape, the metaverse will offer its inhabitants an online experience as rich as, and intimately linked with, their lives in the physical realm. Indeed, these bold pioneers will be able to immerse themselves in the metaverse through all manner of devices, including VR headsets and 3D-printed wearables, as well as technological standards and networks like blockchain and 5G. Meanwhile, the metaverse’s smooth functioning and capacity to expand boundlessly will depend on a durable base of computing power.
The metaverse’s development has taken a bifurcated path. On the one hand, centralized metaverse experiences, like Facebook Horizon and Microsoft Mesh, aim to build standalone worlds whose territory lies entirely within proprietary ecosystems. On the other hand, decentralized projects seek to equip their users with the tools to create, exchange and own digital goods, secure their data, and interact with each other outside the confines of corporate systems.
In both cases, though, the metaverse is not a mere platform, game, or social network; it is potentially every online platform, game and social network used by people around the world all bundled together in one landscape of virtual worlds owned by no one user and by every user at the same time.
In our opinion, the metaverse comprises five layers stacked on top of each other. The most elemental layer is infrastructure — the physical technologies that support the metaverse’s functioning. These include technological standards and innovations like 5G and 6G networks, semiconductors, tiny sensors known as MEMS and Internet data centers (IDCs).
The protocol layer comes next. Its components are the technologies, like blockchain, distributed computing and edge computing, that ensure the efficient and effective computing power distribution to end users and individuals’ sovereignty over their own online data.
Human interfaces make up the third layer of the metaverse. These include devices — like smartphones, 3D-printed wearables, biosensors, neural interfaces, and AR/VR enabled headsets and goggles — that serve as our entry points into what will one day be a collective of persistent online worlds.
The creation layer of the metaverse stacks on top of the human interface stratum, and is made up of top-down platforms and environments, like Roblox, Shopify and Wix, designed to give users tools with which to create new things.
Finally, the aforementioned experience layer completes the metaverse stack, lending the metaverse’s working parts a social, gamified exterior. The components of the experience layer range from non-fungible tokens (NFTs) to e-commerce, e-sports, social media and games.
The sum of these five layers is the metaverse, an agile, persistent, and interconnected patchwork of virtual worlds standing shoulder-to-shoulder in one contiguous universe.
B. Limitations of the metaverse development
Today, the world’s most popular online worlds, like Fortnite and Roblox, cannot support the radical accessibility, connectivity and creativity that will define the metaverse of tomorrow. Metaverse platforms face an enormous challenge: Constricted by a limited supply of computing power, they fall short of delivering a true metaverse experience to their users.
Although high profile projects — such as Facebook’s upcoming Horizon project and Mesh, Microsoft’s foray into the world of holoporting and virtual collaboration — have the backing of leading cloud services, the virtual worlds they offer users will still be covered in red tape, highly centralized and lacking interoperability.
For example, Roblox, which has more than 42 million daily active users, can only support a few hundred concurrent users in a single virtual world. This is a far cry from the metaverse vision of thousands or even millions of users interacting simultaneously in the same virtual space.
Another limitation is the high cost of computing power. Centralized cloud providers charge premium prices for the computing resources needed to run metaverse applications, making it difficult for small developers and startups to enter the space. This creates a barrier to innovation and limits the diversity of experiences available in the metaverse.
Furthermore, the current infrastructure is not designed to handle the unique demands of metaverse applications. These applications require low latency, high bandwidth, and real-time processing capabilities that are beyond the reach of many existing systems. This results in a subpar user experience, with lag, buffering, and other performance issues.
C. Our solution: the computecoin network
Computecoin network is designed to address these limitations by providing a decentralized, high-performance infrastructure for the metaverse. Our solution leverages the power of decentralized clouds and blockchain technology to create a more accessible, scalable, and cost-effective platform for metaverse applications.
The key innovation of Computecoin network is its ability to aggregate computing resources from a global network of decentralized clouds and data centers. This allows us to provide a virtually unlimited supply of computing power at a fraction of the cost of centralized providers.
By offloading computation to a proximity network of nearby decentralized clouds, we can minimize latency and ensure real-time performance for metaverse applications. This is critical for immersive experiences like AR/VR, where even a small delay can break the illusion of reality.
The two-layer architecture of Computecoin network — PEKKA and MCP — provides a comprehensive solution for the metaverse. PEKKA handles the aggregation and scheduling of computing resources, while MCP ensures the security and authenticity of computations through its innovative Proof of Honesty consensus algorithm.
D. Paper organization
The remainder of this paper is organized as follows: In Section II, we provide a detailed overview of PEKKA, including its architecture, resource aggregation capabilities, and computation offloading mechanisms. Section III focuses on the Metaverse Computing Protocol (MCP), with an in-depth explanation of the Proof of Honesty consensus algorithm. Section IV discusses how AI-powered self-evolution will enable Computecoin network to continuously improve and adapt to changing demands. In Section V, we describe the tokenomics of CCN, including token allocation, stakeholder rights, and the mining and staking mechanisms. Section VI lists our publications related to Computecoin network. Finally, Section VII concludes the paper with a summary of our vision and future plans.
II. PEKKA
A. Overview
PEKKA (Parallel Edge Computing and Knowledge Aggregator) is the first layer of the Computecoin network. It serves as an aggregator and scheduler that seamlessly integrates decentralized clouds and dynamically offloads computation to a proximity network. The primary goal of PEKKA is to provide a unified interface for accessing and utilizing computing resources from various decentralized cloud providers.
PEKKA is designed to address the fragmentation of the decentralized cloud ecosystem. Currently, there are numerous decentralized cloud providers, each with its own API, pricing model, and resource specifications. This fragmentation makes it difficult for developers to leverage the full potential of decentralized computing.
By aggregating these resources into a single network, PEKKA simplifies the process of deploying and scaling metaverse applications. Developers can access a global network of computing resources through a unified API, without having to worry about the underlying infrastructure.
B. Aggregation of decentralized clouds
PEKKA aggregates computing resources from a variety of decentralized cloud providers, including Filecoin, Crust, and others. This aggregation process involves several key steps:
1. Resource discovery: PEKKA continuously scans the network to identify available computing resources from various providers. This includes information about the type of resources (CPU, GPU, storage), their location, and their current availability.
2. Resource validation: Before adding resources to the network, PEKKA validates their performance and reliability. This ensures that only high-quality resources are included in the network.
3. Resource indexing: Validated resources are indexed in a distributed ledger, which serves as a transparent and immutable record of all available resources in the network.
4. Pricing normalization: PEKKA normalizes the pricing models of different providers, making it easy for users to compare and select resources based on their needs and budget.
5. Dynamic resource allocation: PEKKA continuously monitors the demand for computing resources and adjusts the allocation accordingly. This ensures that resources are used efficiently and that users have access to the resources they need when they need them.
The aggregation process is designed to be decentralized and trustless. No single entity controls the network, and all decisions are made through a consensus mechanism. This ensures that the network remains open, transparent, and resilient.
C. Computation offloading to a proximity network
One of the key features of PEKKA is its ability to offload computation to a proximity network of nearby decentralized clouds. This is critical for metaverse applications, which require low latency and real-time processing.
Computation offloading involves transferring computational tasks from a user's device to a nearby node in the network. This reduces the burden on the user's device and ensures that tasks are processed quickly and efficiently.
PEKKA uses a sophisticated algorithm to determine the optimal node for each task. This algorithm takes into account several factors, including the node's proximity to the user, its current load, its performance capabilities, and the cost of using the node.
The offloading process is transparent to the user and the application developer. Once a task is offloaded, PEKKA monitors its progress and ensures that the results are returned to the user in a timely manner.
C1. Offloading function 1
The first offloading function is designed for latency-sensitive tasks, such as real-time rendering and interactive applications. For these tasks, PEKKA prioritizes proximity and speed over cost.
The algorithm works as follows: When a latency-sensitive task is received, PEKKA identifies all nodes within a certain geographic radius of the user. It then evaluates these nodes based on their current load and processing capabilities. The node with the lowest latency and sufficient capacity is selected to process the task.
To minimize latency further, PEKKA uses predictive analytics to anticipate future demand. This allows the network to pre-position resources in areas where demand is expected to be high, ensuring that low-latency processing is always available.
C2. Offloading function 2
The second offloading function is designed for batch processing tasks, such as data analysis and content rendering. For these tasks, PEKKA prioritizes cost and efficiency over speed.
The algorithm works as follows: When a batch processing task is received, PEKKA identifies all nodes in the network that have the necessary resources to process the task. It then evaluates these nodes based on their cost, availability, and historical performance. The node that offers the best combination of cost and efficiency is selected to process the task.
For large batch processing tasks, PEKKA can split the task into smaller sub-tasks and distribute them across multiple nodes. This parallel processing approach significantly reduces the time required to complete large tasks.
III. Metaverse Computing Protocol
A. Overview
The Metaverse Computing Protocol (MCP) is the second layer of the Computecoin network. It is a layer-0.5/layer-1 blockchain that provides the security and trust infrastructure for the network. MCP is designed to ensure that the results of computations performed on the decentralized cloud network are authentic and reliable.
One of the key challenges in decentralized computing is ensuring that nodes perform computations correctly and honestly. In a trustless environment, there is no guarantee that a node will not tamper with the results of a computation or claim to have performed work that it did not do.
MCP addresses this challenge through its innovative Proof of Honesty (PoH) consensus algorithm. PoH is designed to incentivize nodes to act honestly and to detect and punish nodes that act maliciously.
In addition to providing security and trust, MCP also handles the economic aspects of the network. It manages the creation and distribution of CCN tokens, which are used to pay for computing resources and to reward nodes for their contributions to the network.
B. Consensus: Proof of Honesty (PoH)
Proof of Honesty (PoH) is a novel consensus algorithm designed specifically for the Computecoin network. Unlike traditional consensus algorithms like Proof of Work (PoW) and Proof of Stake (PoS), which focus on validating transactions, PoH is designed to validate the results of computations.
The core idea behind PoH is to create a system where nodes are incentivized to act honestly. Nodes that consistently provide accurate results are rewarded with CCN tokens, while nodes that provide inaccurate results are penalized.
PoH works by periodically sending "phishing tasks" to nodes in the network. These tasks are designed to test the honesty of the nodes. Nodes that correctly complete these tasks demonstrate their honesty and are rewarded. Nodes that fail to complete these tasks or provide incorrect results are penalized.
B1. Algorithm overview
The PoH algorithm consists of several key components: the phishing-task repository, the task scheduler, the result verifier, the judgment system, and the incentive protocol.
The algorithm works as follows: The task scheduler selects nodes from the network to perform computational tasks. These tasks include both real user tasks and phishing tasks from the phishing-task repository. Nodes process these tasks and return the results to the result verifier.
The result verifier checks the results of both real tasks and phishing tasks. For real tasks, the verifier uses a combination of cryptographic techniques and cross-validation with other nodes to ensure accuracy. For phishing tasks, the verifier already knows the correct result, so it can immediately detect if a node has provided an incorrect result.
The judgment system uses the results from the verifier to determine which nodes are acting honestly and which are not. Nodes that consistently provide correct results are rewarded with CCN tokens, while nodes that provide incorrect results are penalized by having their stake confiscated.
Over time, the algorithm adapts to the behavior of nodes. Nodes that have a history of honesty are trusted with more important tasks and receive higher rewards. Nodes that have a history of dishonesty are given fewer tasks and may eventually be excluded from the network.
B2. Phishing-task repository
The phishing-task repository is a collection of precomputed tasks with known results. These tasks are designed to test the honesty and competence of nodes in the network.
The repository contains a wide variety of tasks, including simple calculations, complex simulations, and data processing tasks. The tasks are designed to be representative of the types of tasks that nodes will encounter in the real network.
To ensure that nodes cannot distinguish between phishing tasks and real tasks, the phishing tasks are formatted identically to real tasks. They also cover a similar range of difficulty levels and computational requirements.
The repository is continuously updated with new tasks to prevent nodes from memorizing the results of existing tasks. New tasks are added by a decentralized group of validators, who are rewarded with CCN tokens for their contributions.
The selection of tasks from the repository is done randomly to ensure that nodes cannot predict which tasks will be phishing tasks. This random selection process is designed to make it difficult for malicious nodes to game the system.
B3. Task scheduler
The task scheduler is responsible for distributing tasks to nodes in the network. It plays a critical role in ensuring that tasks are processed efficiently and that the network remains secure.
The scheduler uses a reputation system to determine which nodes are eligible to receive tasks. Nodes with a higher reputation (i.e., a history of providing correct results) are more likely to receive tasks, especially high-value tasks.
When distributing tasks, the scheduler takes into account several factors, including the node's reputation, its processing capabilities, its location, and its current load. This ensures that tasks are assigned to the most appropriate nodes.
For real user tasks, the scheduler may assign the same task to multiple nodes to enable cross-validation. This helps to ensure that the results are accurate, even if some nodes act maliciously.
For phishing tasks, the scheduler typically assigns each task to a single node. This is because the correct result is already known, so there is no need for cross-validation.
The scheduler continuously monitors the performance of nodes and adjusts its task distribution algorithm accordingly. This ensures that the network remains efficient and responsive to changing conditions.
B4. Result verification
The result verification component is responsible for checking the accuracy of the results returned by nodes. It uses a combination of techniques to ensure that the results are both correct and authentic.
For phishing tasks, verification is straightforward: the verifier simply compares the result returned by the node with the known correct result. If they match, the node is considered to have acted honestly. If they do not match, the node is considered to have acted dishonestly.
For real user tasks, verification is more complex. The verifier uses several techniques, including:
1. Cross-validation: When the same task is assigned to multiple nodes, the verifier compares the results. If there is a consensus among the nodes, the result is considered accurate. If there is a discrepancy, the verifier may request additional nodes to process the task to resolve the conflict.
2. Cryptographic verification: Some tasks include cryptographic proofs that allow the verifier to check the accuracy of the result without reprocessing the entire task. This is particularly useful for complex tasks that would be expensive to reprocess.
3. Spot checking: The verifier randomly selects a subset of real tasks to reprocess itself. This helps to ensure that nodes cannot consistently provide incorrect results for real tasks without being detected.
The verification process is designed to be efficient, so that it does not introduce significant overhead to the network. The goal is to provide a high level of security while maintaining the performance and scalability of the network.
B5. Judgement
The judgment system is responsible for evaluating the behavior of nodes based on the results of the verification process. It assigns each node a reputation score, which reflects the node's history of honesty and reliability.
Nodes that consistently provide correct results see their reputation scores increase. Nodes that provide incorrect results see their reputation scores decrease. The magnitude of the change depends on the severity of the infraction.
For minor infractions, such as an occasional incorrect result, the reputation score may decrease slightly. For more serious infractions, such as consistently providing incorrect results or attempting to game the system, the reputation score may decrease significantly.
In addition to adjusting reputation scores, the judgment system can also impose other penalties. For example, nodes with very low reputation scores may be temporarily or permanently excluded from the network. They may also have their staked CCN tokens confiscated.
The judgment system is designed to be transparent and fair. The rules for evaluating node behavior are publicly available, and the system's decisions are based on objective criteria.
B6. Incentive protocol
The incentive protocol is designed to reward nodes that act honestly and contribute to the network. It uses a combination of block rewards, transaction fees, and task completion rewards to incentivize desirable behavior.
Block rewards are issued to nodes that successfully validate transactions and create new blocks in the MCP blockchain. The amount of the reward is determined by the network's inflation schedule.
Transaction fees are paid by users to have their transactions included in the blockchain. These fees are distributed to the nodes that validate the transactions.
Task completion rewards are paid to nodes that successfully complete computational tasks. The amount of the reward depends on the complexity of the task, the node's reputation, and the current demand for computing resources.
Nodes with higher reputation scores receive higher rewards for completing tasks. This creates a positive feedback loop, where honest behavior is rewarded, and nodes are incentivized to maintain a good reputation.
In addition to these rewards, the incentive protocol also includes mechanisms to prevent malicious behavior. For example, nodes are required to stake CCN tokens to participate in the network. If a node is found to be acting maliciously, its stake may be confiscated.
The combination of rewards and penalties creates a strong incentive for nodes to act honestly and contribute to the network's success.
C. System optimization
To ensure that the Computecoin network is efficient, scalable, and responsive, we have implemented several system optimization techniques:
1. Sharding: The MCP blockchain is divided into multiple shards, each of which can process transactions independently. This significantly increases the throughput of the network.
2. Parallel processing: Both PEKKA and MCP are designed to take advantage of parallel processing. This allows the network to handle multiple tasks simultaneously, increasing its overall capacity.
3. Caching: Frequently accessed data and results are cached to reduce the need for redundant computations. This improves the performance of the network and reduces the cost of using it.
4. Dynamic resource allocation: The network continuously monitors the demand for computing resources and adjusts the allocation of resources accordingly. This ensures that resources are used efficiently and that the network can scale to meet changing demands.
5. Compression: Data is compressed before being transmitted over the network, reducing bandwidth requirements and improving performance.
6. Optimized algorithms: The algorithms used for task scheduling, result verification, and consensus are continuously optimized to improve efficiency and reduce computational overhead.
These optimizations ensure that the Computecoin network can handle the high demands of metaverse applications while maintaining a high level of performance and security.
IV. AI POWERED SELF-EVOLUTION
The Computecoin network is designed to continuously improve and adapt to changing conditions through AI-powered self-evolution. This capability allows the network to optimize its performance, enhance its security, and expand its functionality over time.
At the core of this self-evolution capability is a network of AI agents that monitor various aspects of the network's operation. These agents collect data on network performance, node behavior, user demand, and other relevant factors.
Using machine learning algorithms, these agents analyze the collected data to identify patterns, detect anomalies, and make predictions about future network behavior. Based on this analysis, the agents can suggest improvements to the network's algorithms, protocols, and resource allocation strategies.
Some examples of how AI is used to enhance the network include:
1. Predictive resource allocation: AI algorithms predict future demand for computing resources and adjust the allocation of resources accordingly. This ensures that the network has sufficient capacity to meet demand during peak periods.
2. Anomaly detection: AI agents detect unusual patterns of behavior that may indicate malicious activity. This allows the network to respond quickly to potential security threats.
3. Performance optimization: AI algorithms analyze network performance data to identify bottlenecks and suggest optimizations. This helps to continuously improve the speed and efficiency of the network.
4. Adaptive security: AI agents learn from past security incidents to develop new strategies for protecting the network. This allows the network to adapt to new types of threats as they emerge.
5. Personalized service: AI algorithms analyze user behavior to provide personalized recommendations and optimize the user experience.
The self-evolution process is designed to be decentralized and transparent. AI agents operate within a set of guidelines that ensure their recommendations are aligned with the overall goals of the network. Proposed changes to the network are evaluated by a decentralized community of validators before being implemented.
This AI-powered self-evolution capability ensures that the Computecoin network remains at the cutting edge of technology, continuously adapting to meet the evolving needs of the metaverse.
V. TOKENOMICS
A. CCN token allocation
The total supply of CCN tokens is fixed at 21 billion. The tokens are allocated as follows:
1. Mining rewards: 50% (10.5 billion tokens) are allocated for mining rewards. These tokens are distributed to nodes that contribute computing resources to the network and help secure the MCP blockchain.
2. Team and advisors: 15% (3.15 billion tokens) are allocated to the founding team and advisors. These tokens are subject to a vesting schedule to ensure long-term commitment to the project.
3. Foundation: 15% (3.15 billion tokens) are allocated to the Computecoin Network Foundation. These tokens are used to fund research and development, marketing, and community initiatives.
4. Strategic partners: 10% (2.1 billion tokens) are allocated to strategic partners who provide essential resources and support to the network.
5. Public sale: 10% (2.1 billion tokens) are allocated for public sale to raise funds for the project and distribute tokens to the broader community.
The token allocation is designed to ensure that there is a balanced distribution of tokens among all stakeholders, with a strong emphasis on rewarding those who contribute to the network's growth and security.
B. CCN stakeholders and their rights
There are several types of stakeholders in the Computecoin network, each with their own rights and responsibilities:
1. Miners: Miners contribute computing resources to the network and help secure the MCP blockchain. In return, they receive mining rewards and transaction fees. Miners also have the right to participate in the consensus process and vote on network proposals.
2. Users: Users pay CCN tokens to access computing resources on the network. They have the right to use the network's resources and to receive accurate and reliable results for their computational tasks.
3. Developers: Developers build applications and services on top of the Computecoin network. They have the right to access the network's API and to use its resources to power their applications.
4. Token holders: Token holders have the right to vote on network proposals and to participate in the governance of the network. They also have the right to stake their tokens to earn additional rewards.
5. Foundation: The Computecoin Network Foundation is responsible for the long-term development and governance of the network. It has the right to allocate funds for research and development, marketing, and community initiatives.
The rights and responsibilities of each stakeholder group are designed to ensure that the network remains decentralized, secure, and beneficial to all participants.
C. Mint CCN tokens
CCN tokens are minted through a process called mining. Mining involves contributing computing resources to the network and helping to secure the MCP blockchain.
Miners compete to solve complex mathematical problems, which helps to validate transactions and create new blocks in the blockchain. The first miner to solve a problem is rewarded with a certain number of CCN tokens.
The mining reward decreases over time according to a predefined schedule. This is designed to control the inflation rate of CCN tokens and ensure that the total supply reaches 21 billion over a period of 100 years.
In addition to block rewards, miners also receive transaction fees. These fees are paid by users to have their transactions included in the blockchain.
Mining is designed to be accessible to anyone with a computer and an internet connection. However, the difficulty of the mining problems adjusts dynamically to ensure that new blocks are created at a consistent rate, regardless of the total computing power in the network.
D. Token release plan
The release of CCN tokens is governed by a predefined schedule designed to ensure a steady and predictable supply of tokens into the market.
1. Mining rewards: Mining rewards start at 10,000 CCN per block and decrease by 50% every 4 years. This is similar to the Bitcoin halving mechanism.
2. Team and advisors: Tokens allocated to the team and advisors are released gradually over a period of 4 years, with 25% vesting after 1 year and the remaining 75% vesting monthly over the next 3 years.
3. Foundation: Tokens allocated to the foundation are released gradually over a period of 10 years, with 10% released each year.
4. Strategic partners: Tokens allocated to strategic partners are subject to vesting schedules that vary depending on the partner's agreement, but typically range from 1 to 3 years.
5. Public sale: Tokens sold in the public sale are released immediately, with no vesting period.
This release plan is designed to prevent large amounts of tokens from entering the market suddenly, which could cause price volatility. It also ensures that all stakeholders have a long-term incentive to contribute to the network's success.
E. Mining Pass and staking
Mining Pass is a mechanism that allows users to participate in the mining process without having to invest in expensive hardware. Users can purchase a Mining Pass using CCN tokens, which gives them the right to receive a portion of the mining rewards.
Mining Passes are available in different tiers, with higher-tier passes providing a larger share of the mining rewards. The price of Mining Passes is determined by the market and adjusts dynamically based on demand.
Staking is another way for users to earn rewards. Users can stake their CCN tokens by locking them up in a smart contract for a certain period of time. In return, they receive a portion of the transaction fees and block rewards.
The amount of rewards a user receives from staking depends on the number of tokens they stake and the length of time they stake them for. Users who stake more tokens for longer periods receive higher rewards.
Staking helps to secure the network by reducing the number of tokens available for trading, which makes the network more resistant to attacks. It also provides a way for users to earn passive income from their CCN tokens.
F. Development stage
The development of the Computecoin network is divided into several stages:
1. Stage 1 (Foundation): This stage focuses on developing the core infrastructure of the network, including the PEKKA layer and the MCP blockchain. It also involves building a small test network with a limited number of nodes.
2. Stage 2 (Expansion): In this stage, the network is expanded to include more nodes and support more types of computing tasks. The AI-powered self-evolution capabilities are also introduced during this stage.
3. Stage 3 (Maturity): This stage focuses on optimizing the network and scaling it to handle the high demands of metaverse applications. It also involves integrating the network with other blockchain networks and metaverse platforms.
4. Stage 4 (Autonomy): In the final stage, the network becomes fully autonomous, with the AI agents making most of the decisions about network operations and development. The foundation's role is reduced to providing oversight and ensuring that the network remains aligned with its original vision.
Each stage is expected to take approximately 2-3 years to complete, with regular updates and improvements released throughout the development process.
VI. PUBLICATIONS
The following publications provide additional details about the Computecoin network and its underlying technologies:
1. "Computecoin Network: A Decentralized Infrastructure for the Metaverse" - This paper provides an overview of the Computecoin network, including its architecture, consensus algorithm, and tokenomics.
2. "Proof of Honesty: A Novel Consensus Algorithm for Decentralized Computing" - This paper describes the Proof of Honesty consensus algorithm in detail, including its design, implementation, and security properties.
3. "PEKKA: A Parallel Edge Computing and Knowledge Aggregator for the Metaverse" - This paper focuses on the PEKKA layer of the Computecoin network, including its resource aggregation capabilities and computation offloading mechanisms.
4. "AI-Powered Self-Evolution in Decentralized Networks" - This paper discusses the role of AI in enabling the Computecoin network to continuously improve and adapt to changing conditions.
5. "Tokenomics of Computecoin: Incentivizing a Decentralized Computing Ecosystem" - This paper provides a detailed analysis of the CCN token economy, including token allocation, mining, staking, and governance.
These publications are available on the Computecoin network website and in various academic journals and conferences.
VII. CONCLUSION
The metaverse represents the next evolution of the internet, promising to revolutionize how we interact, work, and play online. However, the development of the metaverse is currently limited by the centralized infrastructure that powers the internet today.
The Computecoin network is designed to address this limitation by providing a decentralized, high-performance infrastructure for the metaverse. Our solution leverages the power of decentralized clouds and blockchain technology to create a more accessible, scalable, and cost-effective platform for metaverse applications.
The two-layer architecture of the Computecoin network — PEKKA and MCP — provides a comprehensive solution for the metaverse. PEKKA handles the aggregation and scheduling of computing resources, while MCP ensures the security and authenticity of computations through its innovative Proof of Honesty consensus algorithm.
The AI-powered self-evolution capability of the network ensures that it can continuously improve and adapt to changing conditions, remaining at the cutting edge of technology.
The tokenomics of CCN are designed to create a balanced and sustainable ecosystem, with incentives for all stakeholders to contribute to the network's success.
We believe that the Computecoin network has the potential to become the foundational infrastructure for the metaverse, enabling a new generation of decentralized applications and experiences. With the support of our community, we are committed to making this vision a reality.
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