Guide to the D.A.G.G.E.R. Litepaper, Part 3

‍Welcome

Welcome to the third and final installment of our three-part “Guide to the Litepaper'' blog series, where we continue on an educational journey into the world of GenesysGo's Directed Acyclic Gossip Graph Enabling Replication Protocol (D.A.G.G.E.R.). In this series, we are breaking down the D.A.G.G.E.R. Litepaper section by section, unraveling the intricate details and uncovering the immense potential of D.A.G.G.E.R. This third post will cover Sections 4 and 5 of the Litepaper, as well as the conclusion. We will offer more clarity on Other Use Cases for D.A.G.G.E.R., Private Cloud Infrastructure, and what it means to “See and Strongly See” inside of D.A.G.G.E.R. It is important to note that while D.A.G.G.E.R. has multiple possible use cases, the principal focus is a consensus engine highly optimized to deliver scalable data storage, and the subsequent downstream improvements this has on applications that care about data-availability. For a deeper dive into the technical specifics of D.A.G.G.E.R. consensus and modules, please refer to the full version of the D.A.G.G.E.R. Litepaper.

Section 4 - Other Use Cases of D.A.G.G.E.R.

GenesysGo’s D.A.G.G.E.R. is, first and foremost, a purpose-built consensus engine for data-heavy applications. However, in the process of solving root cause problems related to high throughput consensus, we captured multiplicative solutions and more versatility. This versatility allows us to theorize numerous applications beyond just storage. It is in the spirit of possibilities, given what we know firsthand in testing D.A.G.G.E.R., that inspires us to share what all it could be capable of beyond its immediate core purpose. Think of D.A.G.G.E.R. as a Swiss army knife for digital infrastructure. While the sole focus of the team at this time is executing our Testnet phases and roadmap for ShdwDrive v2, taking a moment to explain the possibilities of D.A.G.G.E.R. as a consensus engine helps deepen the significance of what we believe is an incredible architecture. While we remain focused on the initiatives highlighted in our Roadmap Overview post, the future is filled with possibilities to further augment ShdwDrive v2!

Section 4.1 - Smart Contract Platform

D.A.G.G.E.R. presents an exciting opportunity to build a versatile, modular smart contract platform. Unlike traditional platforms such as Bitcoin, Ethereum, or Solana, D.A.G.G.E.R.'s unique design inherently incorporates data storage and management. This is a significant advantage as many existing platforms often struggle with handling large volumes of data associated with their platforms, resorting to traditional databases for support. 

With D.A.G.G.E.R., the potential to construct a smart contract platform that is not only efficient but also capable of managing large data sets is within reach. It's not about being 'better' or 'more efficient' than Ethereum or Solana; it's about the flexibility and adaptability that D.A.G.G.E.R. provides; It’s about optimizing a protocol around data availability.

Furthermore, D.A.G.G.E.R. 's design ensures robust safety guarantees, including Byzantine fault tolerance and prevention of Sybil attacks, similar to Proof-of-Stake concepts. It's a system that aligns economic incentives to discourage operators from holding multiple identities and includes penalties as a form of deterrence. 

In essence, D.A.G.G.E.R. offers the potential to deliver a smart contract platform that can efficiently scale data management, making it a compelling proposition in the ever-evolving digital landscape. 

Section 4.2 - Bridges and Oracles

D.A.G.G.E.R. can also be used to build bridges and oracles. These are systems that verify and relay information from one blockchain to another or from a non-blockchain source to a blockchain. It's like having a trusted courier who can quickly and accurately deliver messages between different parties. This opens up a multitude of possibilities for inter-blockchain communication and collaboration, enhancing the overall functionality of the blockchain ecosystem.

Section 5 - Private Cloud Infrastructure

D.A.G.G.E.R. can also be used as an orchestrator of services to ensure the smooth, efficient, and harmonious operation of a private cloud infrastructure. Anecdotally, this was demonstrated by GenesysGo at a 2022 conference by allowing free permissionless deployments of VMs using an alpha version of D.A.G.G.E.R. consensus.

D.A.G.G.E.R.'s design principles of fast storage and swift consensus make it an excellent choice for orchestrating private cloud infrastructure. Whether it's a simple deployment on a set of trusted nodes or a complex network encompassing multiple organizations managing various compute and storage resources, D.A.G.G.E.R. can handle it all. Moreover, D.A.G.G.E.R. can keep track of queues and capacity of resources, ensuring optimal usage and preventing bottlenecks while simultaneously offering secondary storage via ShdwDrive v2 connectivity, all native within the protocol. Incredible things are possible when you deliver data-availability first design principles within a rapid consensus protocol. Let’s dive deeper into D.A.G.G.E.R. consensus in the next section.

To See and Strongly See 

D.A.G.G.E.R. is a way for a network of computers to collectively agree on the order of events and data without relying on any central authority. This allows the network to function in a decentralized way. Each computer in the network creates new "events" which contain data or transactions. The events form a chronological record, like a timeline. When a computer creates a new event, it shares the event with its peer computers in the network. The peers add the new event to their own timeline.

Here's the key part - when adding a new event, each peer computer can calculate whether that event "strongly sees" past events created by other peers. This tells them that enough peers in the network are aware of those past events at the time the new event is created.

For example, if over 2/3 of the peers have a certain past event in their timeline when adding a new event, it is said to "strongly see" that past event. This means there is consensus in the network on the order of those events.

By repeating this process asynchronously, the decentralized network can agree on the order of events over time. No single computer is in charge - they each calculate the visibility of past events independently but arrive at an overall consensus. This allows D.A.G.G.E.R. to record transactions and data in an immutable chronological order without any central party. It enables high throughput and decentralization for things like payment systems, decentralized storage, voting systems, and more. The peers collectively vouch for the accuracy of the record.

Here are some key takeaways from the Litepaper in regard to consensus:

• The ledger is a directed acyclic graph (DAG) built asynchronously by nodes gossiping signed events to each other. This gossip process allows the network to reach consensus without needing global broadcasts or every node directly communicating with every other node.
• Nodes do not need to transmit entire blocks or explicit votes. The graph structure and cryptographic hashes contain the voting information implicitly. This greatly reduces bandwidth demands.
• Consensus is reached on events in parallel rather than in discrete rounds or blocks. This increases throughput and data availability.
• Fork-free operation removes overhead and delays from fork resolution that arise in systems based on chain structures.
• The D.A.G.G.E.R. system is highly bandwidth efficient, which is gained from the consistency of the graphs across all operators coupled with the fact that each event in the graph serves as a vote for multiple blocks.
• Mathematical proofs guarantee Byzantine fault tolerance and fairness in consensus ordering. Malicious actors cannot manipulate the order of transactions.
• The D.A.G.G.E.R. algorithm allows for dynamic membership rules and performs only one-way syncs during gossip
• The asynchronous gossip-based communication pattern provides high resilience. The network can continue reaching consensus efficiently even with packet loss, partitions, failed nodes, etc.
• Dynamic membership allows nodes to join and leave without slowing down consensus. This supports scalability and continuous operation.
• Unlike other systems that must propagate blocks and then transmit O(N^2) or O(N^3) messages to vote on and finalize each block, votes for a particular block in the D.A.G.G.E.R. system are derived from the connectivity of the nodes in the graph and the contents of a small amount of metadata appended to the nodes.
• The core innovations in D.A.G.G.E.R. consensus optimize bandwidth usage for reaching decentralized agreement at high speed. This makes it well-suited for data availability-focused applications like distributed storage networks.

For a fun refresher on the modular design of D.A.G.G.E.R. and the way in which consensus is applied, feel free to review our previously posted Dissecting D.A.G.G.E.R. & The Bee Analogy blog and our D.A.G.G.E.R. Hammer: The Magic Behind a Keypress blog. Both of these help explain in relatable terms how the modules work together to perform consensus across changes in state.

Conclusion

Over the course of this three-part guide, we unpacked the intricacies of GenesysGo's revolutionary D.A.G.G.E.R. consensus protocol. Let's recap some of the most significant takeaways:

• The ShdwDrive v2 implementation showcases D.A.G.G.E.R.'s core purpose for distributed, secure data storage and availability.
• Its unique modular architecture and directed acyclic gossip graph enable high throughput, low latency, and energy efficiency.
• D.A.G.G.E.R. is a versatile consensus engine that can adapt to power decentralized applications such as smart contracts, oracles, bridges, and more.
• ShdwDrive's erasure coding and integration of mobile devices as auditors set a new standard for the resilience and democratization of cloud storage.
• D.A.G.G.E.R. is poised to set a new standard in data capability in decentralized networks across industries.

With a solid understanding of D.A.G.G.E.R. in place, we now turn our sights to the horizon. In our next series, "D.A.G.G.E.R. Versus," we will put this novel consensus engine head-to-head with leading legacy protocols. Stay tuned as we highlight D.A.G.G.E.R.'s advantages and demonstrate how its innovative design overcomes limitations faced by existing systems. The future of decentralized consensus belongs to the next generation of protocols. D.A.G.G.E.R. is poised to lead the pack with its focus on versatility, performance, and data availability. 

Additional Resources

Read the D.A.G.G.E.R. Litepaper: https://github.com/GenesysGo/dagger-litepaper

Play D.A.G.G.E.R. Hammer: https://dagger-hammer.shadow.cloud/

Run a D.A.G.G.E.R. Wield Node: https://docs.shdwdrive.com/wield

‍Learn more about the SHDW Token: https://www.shdwdrive.com/blog/unlocking-the-shdw-token