DAGs Technology: History and Use cases

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thingschain

5 min readOct 15, 2018

Blockchain-free cryptocurrencies are those that use alternative systems in order to function similarly to cryptocurrencies that utilize blockchain technology. DAG stands for Directed Acyclic Graph and can serve as a viable alternative to blockchain technology as shown in cryptocurrencies such as DagCoin, ByteBall, and IOTA.

In terms of decentralized technology, directed acyclic graphs (DAGs) are the new kid on the block. However, DAGs have been used for thousands of years and perhaps even used unknowingly. DAGs are superior to blockchains in a sense that it allows higher throughput, by combining the concepts of blockchains, proof of work and stake, and the longest chain rule with directed acyclic graphs.

In a DAG system, there are no miners and there are no blocks, users confirm each other’s transactions via a process that confirms previous transactions with each new transaction. Because there are no blocks, there is no blocksize issue and therefore, the block scaling debate seen in currencies such as Bitcoin does not exist.

In blockchain technology, transactions are grouped and are confirmed by miners and subsequently added to the chain. In DAG technology, each new transaction confirms at least 1 previous transaction. Transactions are not grouped into blocks (transactions are represented as circles, the red lines represent the confirmation “link” between new transactions and previous transactions).

But the history of DAGs extend back to long before Satoshi first started writing the Bitcoin whitepaper, before Leonhard Euler published his paper on the ‘Seven Bridges of Königsberg’, and even before the Ancient Egyptians laid the first stone of the pyramids. The first use of a DAG is undated, but the concept is so useful, it extends back to the dawn of human existence.

As mentioned before, the publication ‘Seven Bridges of Königsberg’ by Leonhard Euler in 1736 is regarded as the first paper to cover Graph Theory. The seven bridges of Königsberg is a notable problem in the history of mathematics. The challenge is to find a route to cross each of the seven bridges in Königsberg (now Kaliningrad, Russia) once and only once. After simplifying the map of the city to a graph, Euler introduced his formula relating the number of edges, vertices and faces.

From here, Graph Theory has developed into a study of relationships between objects, depicted by mathematical structures. There are many different types of graphs, all with specific definitions, and a DAG is one of them. Now, although graphs were not formally defined until 1736, the ‘Seven Bridges’ problem existed for hundreds of years before and, people had been creating mental and physical representations of the problem. Although there was no formal definition, these representations were graphs. Just as graphs were not defined, yet they were used, DAGs were also not defined, yet they were used!

An ancient use case of DAGs is creating a family tree. Interestingly, the definition of a tree in Graph Theory did not include most family trees. This is because in most family trees stretching back far enough, at some point distant relatives have mated, allowing a common ancestor on both the paternal and maternal sides of the family. This means, a family tree can be considered a DAG–where each node is a person, and each parent-offspring relationship is drawn as an arrow pointing towards the offspring. This forms a graph as shown below, which is directed (the arrows) and acyclic (no person can be a parent of themselves).

Depictions of family trees as DAGs have been recorded in Ancient Rome, by Pliny the Elder who described the graphs decorating the walls of Roman patrician houses. Prior to this, DAGs may not have been recorded, but often described when explaining family histories.

Another historic use case for DAGs is task scheduling where animals and humans innately use DAGs to work out the order of tasks to complete. When completing a job that requires multiple tasks, such as cooking dinner, we make a mental list of the order of tasks. Some tasks cannot begin until others are complete and other tasks can begin at any time — this in itself is a DAG.

In the above DAG, T1 may be to decide which animal to hunt for dinner, task 2 is to hunt the animal, and task 3 which can be done concurrently is to collect firewood. Task 4 is to start the fire. Task 5, to cook the animal, requires both the fire to be burning and the animal to be hunted, and task 6 is to eat the dinner, which needed the animal to be cooked first.

Similar (but more complex) DAGs would have been used for any large task, such as building the pyramids, designing Rome, planning an attack during a war, etc.

What is Radiating Block Graph of Thingschain?

Radiating block graphs are similar to DAGs. A DAG is a finite directed graph with no directed cycles. It consists of finitely many vertices and edges, with each edge directed from one vertex to another.

The key structure which makes DAGs work is a Tangle. The Tangle is a particular kind of directed graph, which holds transactions. Each transaction is represented as a vertex in the graph. When a new transaction joins the tangle, it chooses two previous transactions to approve, adding two new edges to the graph.

Radiating Block graphs also work on a similar concept with multiple nodes and directed connections between them.

Conclusion:

Is DAG the future of cryptocurrencies? Can DAG compete with blockchain technology? Do DAG and blockchain even need to compete, or are they to have totally separate and/or interconnected use cases? If RBG is better, Can it change the world?

Time can only tell what these technologies will be used for and how they will interact with each other. DAG, RBG and blockchain accomplish similar goals with different techniques. There are tradeoffs to both and there many developers on both sides — though it should be noted that there are significantly more developers on the blockchain side.