The unique value proposition and bull case for Constellation Network:
By: Seth V
Tags: Directed Acyclic Graph, Cryptocurrency, Distributed Ledgers, Hypergraph, Constellation Network

Constellation Network is the result of multi-disciplinary mathematical concepts all converging together to create a technology that has the power to change the world. It is truly unprecedented and unparalleled in its elegance and scope. Please join me as I attempt to distill the magnificence imbued in this elegant masterpiece.

Exclusive Technological Differentiators

Essentially, Constellation Network can be classified as next generation distributed ledger tech that is able to reconcile seemingly opposing qualities of distributed and decentralized networks that were previously thought impossible according to thought leaders in the crypto industry who have conceptualized this problem as the “Trilemma”.

A Breakthrough Innovation in Consensus Algorithms

The invention of the Directed Acyclic Hypergraph has no equal on the market. It eliminates the need to compromise or trade-off security, scalability, decentralization, composability, and interoperability. It achieves this through a micro-services architecture which utilizes a concurrent asynchronous byzantine fault tolerant consensus algorithm that is further enhanced by machine learning models to dynamically determine node trustworthiness and network optimization. Constellation refers to this as their Proof of Reputable Observation (PRO) consensus algorithm which automatically prevents forking and enables self-healing of the network through its dynamic multi-level partitioning. This enables unprecedented Sybil attack resistance, to quote Constellation’s CTO & Co-Founder:

“Basically, all it takes is one node in our network, to prevent a sybil attack. Literally if one node has not been compromised or been a part of some kind like collusion attack, this would mean that operators would have to get together and deploy code that is not the correct source code. All it takes is one, because, the fact that any kind of action that could be seen as invalid to invalidate a chain state, is stored directly in chain. So, if you try to read back the state of nodes who perform a sybil attack, it will be read back as an invalid state. So, if all it takes is one node to keep the cluster online, then we can rejoin nodes to that one node, or we can join extra peers to that one node to kick consensus off again, because that node will have forked from the other peers. This also explains how re-download works as well.” — Wyatt Meldman-Floch, CTO & Co-founder (paraphrased for brevity from a technical AMA discussion)

This unique architecture enables nodes at the very edge of the network to validate data just as easily as nodes located at the core, allowing for wide range of horizontal and vertical scalability using devices such as mobile phone to function as a “lite node” or a cloud server running a full node to perform consensus concurrently. You can imagine a scenario where a smart city comprised of various devices such as IoT devices, autonomous vehicles, drones, even satellites, all conducting validation at the edge of the network.

To put this into context from a transactions per second (TPS) perspective, the theoretical throughput based on the number of active mobile devices in 2018 alone would equate to 30 Billion TP/S. This doesn’t even account for other device types running lite nodes nor the most recent number of mobile devices distributed as of 2021. The finality windows per state channel are also configurable which then surface up into the global consensus snapshot for the Hypergraph itself. Ultimately, this is just an example of how the architecture is not bounded to any horizontal or vertical scaling limitations due to the it’s network of DAGs approach to scaling compared to other Layer 1 networks that rely on sharding or Layer 2 networks that introduce centralization risks and off-chain dependencies.

De/Centralize 2018 Conference — https://youtu.be/g-Eza29UN9c?t=128

Validation of Complex Data Structures

The Hypergraph's scope goes way beyond validating a transaction or an account balance on a ledger that current distributed ledgers based on blockchain or directed acyclic graph (DAG) technology are designed to solve. It is the first decentralized network that is capable of validating complex data streams in real time, making it suitable for Big Data and cybersecurity applications that were previously impossible to conceive of with existing technologies. This explains Quant Network and Chainlink’s desire to integrate with Constellation Network to incorporate big data into their oracles which I will elaborate later on in this article.

Slide from Scale By The Bay 2018 Conference — https://youtu.be/iT5TjZGpajM?t=1129

The Hypergraph is flexible enough to validate and model any complex data structure, opening the ability to model and validate data streams originating from other distributed ledger networks such as Ethereum or Bitcoin. This grants these Layer 1 networks the opportunity to take advantage of the unique properties and capabilities of the Constellation Network while allowing for cross chain swapping of tokenized assets, all without the need to perform token wrapping that would normally introduce counter party risk and centralization. This also eliminates the transactions fees associated with wrapping tokens that each network participant would needs to pay. Co-founder of Ethereum, Vitalik Buterin, expressed his concern about wrapped tokens himself:

You can think of Constellation as a “Layer 0” meta-network that can create a true network of networks which effectively creates a decentralized order book of global liquidity from which all DLTs can exchange assets. The technical mechanics of how this is accomplished can be explained with yet another unique innovation known as an emission, which is a data structure that essentially represents an inverse of a transaction (I like to think of it as an anti-transaction) that can serve as a unit of exchange across chains or ledgers. The Hypergraph Transfer Protocol, or HGTP for short, creates a connection between liquidity pools across ledgers by essentially wrapping the entire L1 protocol itself into the Hypergraph, which then enables the emission data structure to be validated as a two sided transaction by converging on a global consensus across ledgers. The concept of an emission data structure is only possible due to the generative economics mathematical framework that has been incorporated into the design of Constellation Network which I will expand upon later in this article.

If you were to try and visualize the network architecture, imagine a network of DAG networks. You have the Hypergraph itself which is a DAG that represents the entire global consensus state and then an infinite amount of independent DAG networks (referred to as “State Channels”) with their own customizable consensus validation criteria occurring asynchronously.

“And so, each state channel could define its own consensus mechanism but it can also choose to simply inherit proof of reputable observation from the L0 is that correct? — Benjamin Diggles, CSO & Co-founder “Proof of reputable observation actually occurs on every L0, however, every single state channel is able to engineer validation criteria that makes sense for them, on their L1. So, basically the L0 is still running a final validation step on the output of an L1 consensus protocol since it’s sort of like that final filter that goes through, but for a developer, in most cases, it’s really simple since you can just copy and paste what we’ve got right now and just change it for their data structures. They can use our L1 and then we can add extra validation logic which you can then embed into a partial function which results in very simple scripting process at that point. The L0 is going to look up what you’ve defined on the L1 and just run that final validation step right at the end before it globally converges.” Wyatt Meldman-Floch, CTO & Co-founder (paraphrased for brevity from Hypergraph Hour 23)

The topological hierarchy of the tech stack can be understood by the following illustration:

Topologically, state channels can be understood as independent Layer 1 directed acyclic graph networks

This is the magic that enables infinite scale. This same structure of complexity is inspired by how nature ultimately organizes itself into complex topological order in the physical world which is an interdisciplinary science studied as Complex Systems Science. I recommend checking out Sante Fe Institute’s book, “Worlds Hidden in Plain Sight”, if it is of further interest.

Visualization of neural-network-assisted stochastic Gas optimization of the network

On-chain Programmability: State Channels vs. Smart Contracts

I won’t elaborate too much on this topic since Andrew Muller did a great write up about this already which you can read here. In short, you can think of state channels as the next generation smart contract in that they can easily model any logic and data structure that can be programmed into one but without their inherent limitations. With state channels you are essentially creating a DAG powered smart contract that can validate any complex data structure and business logic and also serve as an off chain data oracle at the same time, entirely compatible with external enterprise systems and programming languages that are utilized.

Developed using an Accessible, Performant, and Secure Programming Language

The choice of using Java Scala as the programming language allows simple integration into legacy infrastructure and systems while leveraging an army of over 8 million Java developers worldwide. Scala is statically typed and combines object-oriented and functional programming in one concise, high-level language that enables formal verification of code to validate its mathematical correctness. This is required for mission critical applications such as Fintech, Government, and Artificial Intelligence use cases that require extreme level of information assurance and code integrity (minimizes bugs and vulnerabilities).