Unleash resource potential with innovative architecture to drive AO value creation and application innovation

Traditional blockchain technology, represented by Bitcoin and Ethereum, has made remarkable achievements in decentralization, transparency and security, and has promoted the development of encryption technology and applications. However, due to the "blockchain impossible triangle" problem (Figure 1-1), there are obvious bottlenecks in computing performance and resource utilization, which hinders technological innovation and application development, and brings challenges to the encryption industry.

First, let’s analyze the three elements in the “blockchain impossible triangle”:

• Security: Security essentially reflects the consensus requirements, which are specifically reflected in ensuring the consistency, integrity, tamper-proofing, traceability and verifiability of block data. Meeting these characteristics enables blockchain to build a "trustless" strong trust security mechanism. Therefore, the security of consensus is the primary demand of blockchain and the cornerstone of its development.

• Decentralization: Decentralization means that there is no single control point in the system, and power and control are distributed across multiple nodes, which can improve the system's fault tolerance, anti-censorship and security, and prevent single point failures and malicious manipulation. Although a distributed system is not necessarily a decentralized system (for example, a distributed system controlled by a single entity is not a decentralized system), a decentralized system is definitely a distributed system.

• Scalability: In the concept of "blockchain impossible triangle", scalability refers to the ability of distributed system computing performance to expand. For digital systems, everything is computing, and different applications have different computing performance requirements. But in a broad sense, scalability refers to the ability of the system to handle the growing amount of data, transaction volume and number of users, which is not only reflected in TPS, but also in storage capacity, network bandwidth and number of nodes. High scalability can support large-scale applications and user growth. The scalability of distributed systems directly affects the innovation and scale of decentralized applications (DApps) on them.

Among the above three elements, blockchain emphasizes decentralization, strengthens verification and consensus security, but is relatively weak in computing performance. This creates the blockchain impossible triangle problem: when the needs of decentralization and consensus security are met, the scalability of computing will be limited, such as Bitcoin. This means that under such a system framework, the distributed system of blockchain is difficult to support application innovation with high computing performance, or cannot meet the scale requirements of applications, such as AI big data models, graphics rendering, on-chain games, and large-scale social interactions.

The above mainly analyzes the computing performance expansion problem brought about by the impossible triangle of blockchain. What is the root cause of this problem? Next, we will start from the formation process of the block and explore the relationship between the various elements in the block.

In blockchain technology, a "block" refers to a data set formed by packaging a series of verified transaction data within a specific time interval . This concept includes the following key elements and their interrelationships:

• Consensus (data): Verified transaction data with state consistency, that is, the consensus data formed in the block.

• Block space: refers to the storage space for transaction data. These transactions are encapsulated in blocks, and the number of transactions that can be stored is limited by the block size (set by the system or limited by the total gas fee of the block), which means that the storage space on the chain is a limited resource, which in turn affects the scalability of the application.

• Computing performance: The number of transactions packaged divided by the block time is the number of transactions processed per second, that is, TPS (transactions per second) = number of transactions in a block / block time. Computing performance is related to the consensus process and storage space.

From the above analysis, we can see that the consensus, storage space and computing performance in the block are interrelated and form a restrictive relationship. While pursuing consistent consensus, the blockchain not only constrains the scalability of a single block storage space, but also limits the expansion of computing performance. This is the root cause of the blockchain impossible triangle problem.

Further analysis shows that in the process of block formation, the blockchain system builds three global, system-level resources: data (consensus) resources, storage resources, and computing resources . However, the impossible triangle problem limits the role and scalability of these three resources, forming a resource bottleneck and making it difficult to fully unleash their potential. If there is a way to break this constraint, will it bring a new resource-driven development situation to the blockchain?

This is the core question that this article is thinking about and aims to find the answer to. Research shows that from the SCP paradigm, the super-parallel computing model Actor to the SSI distributed system architecture, a complete technical chain has been formed in the engineering practice of AO + Arweave, breaking the impossible triangle problem of blockchain, fully releasing the resource potential of blockchain and distributed systems, and providing empowerment in practice, thus opening up a new development path for the value creation and large-scale application of Web3 .

AO (Super Parallel Computing Network) is built on Arweave and realizes the engineering application of the Storage-based Consensus Paradigm (SCP). As shown in the following figure:

Based on the core concept of SCP, the AO + Arweave system architecture achieves an effective separation between on-chain storage (consensus) and off-chain computing:

• Storage level: The storage resources provided by Arweave are responsible for the permanent storage of data. Blockchain technology ensures the traceability and immutability of on-chain data, achieves data consistency and high availability, and embodies the concept of "storage is consensus".

• Computing layer: Computing tasks are migrated to the off-chain and decoupled from the storage (consensus) layer. This design makes computing performance not directly constrained by the on-chain consensus, and can be infinitely expanded by adding off-chain computing nodes, greatly improving processing efficiency and system flexibility.

• Overall effect: Arweave's storage public chain maintains the system's decentralization and data consensus security, while AO guarantees unlimited scalability of computing performance off-chain. This structure ensures that the entire AO + Arweave system's needs in terms of decentralization, consensus security, and computing performance scalability are met, effectively solving the challenge of the blockchain's impossible triangle.

The above-mentioned features based on SCP implementation play an important role in the application practice of the system. They make storage, computing and data (consensus) system elements that are both interconnected and independent of each other, and become global, system-level resources, as shown in Figure 2-2:

Utilizing the above-mentioned system-level resources and distributed characteristics, AO is built on the Arweave storage public chain to form a cloud computing network. Similar to traditional Web2 cloud computing, AO theoretically has unlimited scalability in computing and storage resources and can support huge data resources. However, AO is unique in that it has established a decentralized, globally consistent, trusted computing platform based on the storage consensus paradigm.

• First, Arweave provides a permissionless, permanent storage service for users around the world, building a consensus data foundation that does not rely on trust.

• Secondly, AO stores the source code of various applications on the Arweave chain, which can be downloaded and run locally; its input comes from trusted data on the chain, and under fixed input and execution logic, the consistency and predictability of the output results are guaranteed.

• Finally, any client can perform consistency verification because under the same input parameters and execution logic, its calculation output results must be consistent, thus ensuring credibility.

It can be seen that the source program, input and output are all deterministic, and AO has built a trusted computing system based on storage consensus.

The storage consensus paradigm is different from the usual node consensus system. In the storage consensus paradigm, calculation, verification and consensus are all off-chain, and the final consensus data is submitted to the chain for storage, becoming the system's availability layer, consensus layer and settlement layer . In other words, with the support of SCP, computing performance is no longer restricted by consensus and can be infinitely expanded off-chain. This mechanism provides the feasibility of creating a highly parallel and distributed architecture that supports high-performance computing for the AO network.

So, how did AO evolve into a decentralized world computer with distributed deployment and high parallel operation? This is mainly due to the Actor model, network communication unit and distributed architecture based on SSI implementation.

The name of the AO network comes from "Actor Oriented", which means it is a super parallel computing network. This name comes from the Actor model used at its core, which sets the basic structure of parallel computing in the system.

In the Actor model, "actor" is the basic unit of parallel computing, which consists of three major elements: state, behavior, and mailbox. These three elements and their interactions constitute the core concept of the Actor model, as shown in Figure 3-1:

The model defines the core components and interaction rules of the system. An actor can be viewed as an independent, concurrently active entity that can receive messages, process messages, send messages, and dynamically create new actors. The model has the following characteristics:

• Asynchronous communication : Multiple actors send messages in a unified format in a point-to-point manner. The sending and processing of messages are asynchronous. This communication method is naturally suitable for the interaction between nodes in a distributed system.

• Parallel operation : Each actor is independent and has no shared state, so there is no need to worry about the state of other actors affecting themselves. Each actor can handle its own tasks independently to achieve true parallel operation.

• Distributed deployment : Actors can be deployed and scheduled to run in different CPUs, nodes, or even different time slices without affecting the final result.

• Scalability : Due to its distributed nature and loosely coupled design, the Actor model can be flexibly expanded horizontally by adding nodes and dynamic load balancing.

In short, the Actor model optimizes parallel and concurrent issues with its elegant processing mechanism, and is particularly suitable for building distributed systems and high-concurrency applications. The AO network adopts the Actor model as the architectural basis for parallel computing, thereby achieving efficient asynchronous communication, parallel operation, distributed deployment, and excellent scalability.

The Actor model provides a framework for parallel computing, and the communication network unit of AO embodies the specific practice of this model . These network units include the message unit (MU), the scheduling unit (SU), and the computing unit (CU). Each unit is an independent "actor" that collaborates and synchronizes through messages in a unified format (ANS-104). Figure 3-2 shows the basic functions and message interaction process of these network units.

In the AO network, starting an application will trigger the start of one or more processes, and the system will configure resources such as memory, virtual machines, and communication network units for each process. Interactions between processes are all completed through messages. First, messages from users or other processes are sent to MU, which then forwards the messages to SU for sorting. The sorted messages and their results will be permanently stored on Arweave, and a CU in the CU cluster competing for computing rights will perform state calculations, which means that the process can run on any computing node, showing typical decentralized parallel computing characteristics. After the calculation is completed, the CU will return the results to the SU in the form of a signed certificate to ensure the accuracy and verifiability of the calculation results, and finally upload them to Arweave by the SU. The complete data set formed by each process - including the initial state, processing process, and final result - will be permanently stored on Arweave, becoming consensus data that can be retrieved, verified, and used by others.

Figure 3-3 shows the specific application scenario of the AO network processing token transfer requests, clearly depicting the composition and communication process of each modular network unit, as well as the distributed storage mechanism formed by the interaction with Arweave.

The AO system makes comprehensive use of computing resources (distributed CU clusters), storage resources (distributed Arweave nodes), and data resources (long-term available data stored in Arweave), laying the foundation for AO to become a global computing platform . Built on the Actor model, AO's computing network not only has the characteristics of asynchronous communication, parallel operation, and distributed deployment, but also has excellent scalability. It is a truly decentralized, distributed, and parallel computing network.

In the previous section, we explored the composition and working principle of the AO network communication unit. In this section, we will analyze the security of this network in depth, which is closely related to the native token $AO of the AO protocol. This analysis will echo the content of "Security Resources" in Section 2.2, focusing on the customizable security and security resources in the AO network.

The network communication unit composed of MU, SU and CU is the core component of the AO computing network. It builds the operating mechanism of the decentralized world computer and forms three types of system-level resources: computing, storage and data. This is the basis of the technical model and resource model in the AO network. Based on the technical model and resource model, the AO system creates a demand-driven and customizable security mechanism. This is an economic model built on the protocol's native token $AO, which brings security guarantees through economic games and thus provides a secure market in AO.

To facilitate understanding, the security mechanism in AO is simplified into several core elements and their interrelationships from the user's perspective: customized requirements, security/economic resources, security mechanisms, and security competition market.

Figure 3-4 describes the relationship between the various elements in the AO network security mechanism:

• Customized requirements: As a super parallel computing platform, each node in AO runs various processes independently and in parallel to process different types of data. These different data transaction scenarios have different requirements for system latency, cost, and efficiency, which requires AO's security model to be flexible and able to customize security policies according to needs. Users can customize the specific security level required for each message, thereby promoting the customization and effective allocation of security resources.

• Security/Economic Resources: $AO is the native token of the protocol. As a circulating public value unit and economic resource, it supports the economic game mechanism of all security mechanisms in the AO network.

• Security Mechanism: In each process of AO, nodes including MU, SU and CU need to stake $AO to participate in the security mechanism. By staking economic value, the system manages funds and imposes fines according to the rules to prevent malicious behavior. For example, if MU signs an invalid message or CU provides an invalid signature certificate, the system will cut its staked assets.

• Security Competition Market: Since security is purchased on a per-message basis, different messages correspond to different pledge requirements, resulting in a dynamic competitive market. The price of security is determined by market supply and demand, rather than fixed network rules. This market competition mechanism promotes the efficient pricing and allocation of security resources, providing tailored security.

In summary, the decentralized peer-to-peer market structure of the AO network essentially enables nodes to independently set the fees for their messaging services, which adapts to the different security requirements of different data transactions and reflects the efficiency of the system's response to specific security. This flexibility enables it to dynamically adapt to changes in market demand and supply, promote competition and improve response efficiency, thereby achieving an efficient equilibrium in the market.

As a tool for economic game, the liquidity of $AO has established a comprehensive and real-time token valuation framework while establishing a security mechanism, providing a solid foundation for the effective valuation of tokens. A $AO token economic model with a complete valuation framework and indicators will undoubtedly further enhance the security of the AO network.

In the previous discussion, we have explained the basic framework provided by the Actor model for AO network parallel computing, and how the network communication units composed of MU, SU, and CU specifically implement this model. These communication units are deployed on different heterogeneous nodes in the distributed network, so that the process operation is not restricted by a specific physical location and seamless user interaction is achieved through the network. All of this together forms a unified computing environment and realizes a single system image (SSI), which is the basis for the AO network to support countless processes. This section will explore the definition of SSI and its specific role in AO.

Single System Image (SSI) is a core concept in distributed computing. It integrates physically separated heterogeneous computing resources into a unified resource pool through virtualization technology. This integration not only improves the abstraction level of the system, but also greatly optimizes the user experience. With SSI, even though the system may consist of multiple servers, distributed databases, or multiple networks, users perceive it as operating a single computer.

Typically, the SSI structure includes a user layer, a unified interface, a resource management layer, computing nodes, and a storage layer. Its structural diagram is shown in Figure 4-1.

Users interact with the SSI system at the user level through the client or web front end. The unified interface is responsible for receiving user requests and distributing them to the resource management layer. The resource management layer schedules distributed computing nodes and storage resources to perform parallel computing tasks or read and write data.

SSI provides a feasible solution to the current problem of coexistence of multiple public chains. For example, due to the rapid development of the Ethereum ecosystem, it faces congestion, low efficiency and high costs. Layer2, as the main solution to these scalability problems, introduces new challenges. While each Layer2 chain repeatedly builds infrastructure, it also leads to liquidity dispersion and asset cross-chain risks, increases the complexity and participation threshold for users to switch between chains, and seriously affects the user experience and the scale development of applications.

Public chains such as Solana and Polkadot have realized these problems and made adjustments based on the original architecture. However, AO adopted SSI's distributed architecture at the beginning of its design, showing foresight and foresight.

Using the Actor model, AO's network communication units are hosted on a set of heterogeneous nodes in a distributed network. These nodes may be distributed in various regions around the world, including servers of various types and functions. The AO computing network based on the Actor model is a decentralized distributed network that requires a unified architecture for integration to provide consistent availability and user experience.

When a user starts an AO process through the front end, the system will configure the different resources required to handle tasks such as message delivery, transaction sorting, and state calculation. For users, the underlying complex distributed architecture is abstracted, and even a large cluster of nodes is like a single computer. This is because the AO system uses SSI to integrate the complex components of the distributed system and achieves a unified computing environment through modularization. In other words, through the SSI architecture, AO integrates multiple distributed computing nodes into a unified resource, providing users with a transparent, efficient, scalable and unified computing platform.

In summary, through the combination of SCP, Actor and SSI, AO has built an innovative architecture, creating three scalable system-level resources for the system: computing, storage and data (consensus), as well as a security resource supported by $AO. As a core production factor, resources play a key role in promoting technological progress, stimulating application innovation, and improving economic efficiency. By clarifying the resource elements in the AO + Arweave system, we can optimize resource planning and management, use resources to drive technology and application innovation, accelerate the value creation of Web3, and promote the growth of the crypto economy.

Here, we make a summary:

• Decentralized World Computer: AO integrates scalable computing, storage, and data resources to provide a unified decentralized computing platform for all applications, with verifiable and trust-minimized features. Applications only need to focus on business innovation and avoid reinventing the wheel, making AO a public infrastructure for application innovation.

• On-chain shared data resource library: Arweave can permanently store almost all types of data, becoming a "Library of Alexandria" that will never disappear. Whether it is financial data or non-financial data, its tamper-proof and verifiable characteristics make it a public commodity that can provide consensus value and support combinatorial innovation.

• Customizable security facilities: AO can provide customized security mechanisms for customers and applications based on different data types and values, achieving a balance between security, cost and efficiency.

• Bridge between Web2 and Web3: AO runs off-chain and can be seamlessly integrated with on-chain and off-chain systems, becoming a bridge between Web2 and Web3. Any Web2 application can start a process in AO through API and messaging mechanisms, call the network unit in AO to perform calculations, and customize its security mechanism.

Since the development of blockchain, the application of public chains such as Bitcoin, Ethereum, Solana, etc. is still biased towards the financial field, such as asset issuance, trading, mortgage lending, derivatives, etc., which makes many people mistakenly believe that the role of blockchain is limited to this.

However, the innovative architecture of AO + Arweave has added new feasibility to the technological innovation and application development of blockchain. In addition to supporting the financial innovations that most public chains have, AO, as a universal world computer, supports all data types and corresponding application innovations, especially non-financial data-driven application innovations.

• Loading AI models: The AO + Arweave architecture provides unlimited computing, storage, and data resources. With the support of three key technologies: WASM64, WeaveDrive, and the Llama.cpp large language model inference engine, AO can directly run a variety of open source large language models in smart contracts, such as Llama 3 and GPT-2, enabling smart contracts to directly process complex data and make decisions, such as the on-chain autonomous virtual world Llama Land realized by the AI-driven Llama 3 model.

• Creating Agents and AgentFi: Based on the reasoning capabilities of AI models, the ability of AO processes to respond to implicit messages based on time, wake themselves up and perform actions, and the ability to "subscribe" to a process by paying a fee to MU to trigger calculations at an appropriate frequency, AO supports Agents and AgentFi that can meet complex business logic, predefined requirements and diversified autonomous strategies.

• Copyright management and creator market (ContentFi): Arweave stores various types of data in the form of atomic assets. The data is easy to identify and ownership is confirmed. It can be monetized as a new form of digital asset. It can achieve price discovery through circulation and trading in the market, establish a clear profit distribution and collaboration model, and provide support for copyright management and creator market.

• Permaweb, the next-generation Internet framework: Different from the three-layer structure of the application layer, service layer, and storage layer of the traditional Web2 Internet, Permaweb achieves permanent storage of all content by replacing the storage layer with Arweave's permanent storage solution, and stores it in Arweave in the form of atomic assets. Based on SCP, various applications that support AO hyperparallel computing are built at the application layer to create a new generation of Internet framework that is always online and decentralized. Although this framework is integrated with Web2 and the experience is the same as Web2, there are significant differences between the two. Permaweb is not a "walled garden". It provides a fair and open environment for developers, operators, and users: users own and control their own data; data can flow freely between different applications; developers and operators can use data to conduct business within established rules without special permission, thereby promoting mutual benefit and win-win results among all parties.

The above are several typical application innovation directions that AO can support. Of course, AO can support application innovations of more data types and wider scenarios. Although the AO ecosystem is still young and technology and application innovation still need time to test, we prefer to evaluate the significance and value of these innovations from the stage of development of the entire Web3 industry and the characteristics of the Web2 system.

Currently, the Web3 industry is exploring feasible paths for large-scale adoption, and many blockchains are working towards this end. For example, TON has combined with Telegram to guide the transition from real Web2 users to real Web3 applications, with the intention of realizing the value conversion of traffic to liquidity on a large scale; CKB has become the L2 of Bitcoin and is building a lightning network based on CKB, intending to bring high-frequency, small-amount, large-scale peer-to-peer payments.

From the perspective of industry development, AO + Arweave redefines the implementation framework of decentralized computers, brings system flexibility, security and economic efficiency with innovative architecture, builds scalable system-level resources, sustainably releases resource potential, drives technological and application innovation, realizes value creation and transfer, promotes the integration of Web3 and Web2, and provides a feasible path for Web3 to move towards large-scale adoption.