Hedera and Hedera Hashgraph technology
Hedera has its origins back in 2012 when Dr. Leemon Baird first began developing his algorithmic model. He aimed to find a revolutionary approach to scalability problems and find a golden middle in distributed consensus security. By the way, Baird was a professor of computer science at the US Air Force Academy and holds a Ph.D. in computer science. Baird was also co-founder and CTO of identity management companies: Trio Security and BlueWave Security. For four years, he worked diligently on his brainchild, leading to the first technical documentation.
The document was published in 2016, and was called: “Hashgraph Consensus: Fair, Fast, Byzantine Fault Tolerance”. From the title, it can be inferred that it tried to find a solution to the Byzantine fault tolerance (Explanation: Byzantine fault tolerance is a condition of a computer system, particularly distributed computing systems, where components may fail and there is imperfect information on whether a component has failed. The term takes its name from an allegory, the “Byzantine Generals Problem”, developed to describe a situation in which, in order to avoid catastrophic failure of the system, the system’s actors must agree on a concerted strategy, but some of these actors are unreliable).
Thanks to the published scientific work, many experts view Hashgraph as the first technology that has managed to tackle basic blockchain problems. The system is closely tied to a high level of security, and it can be said that the scalability of the project, indeed, is at an appropriate level. In 2018, Leemon Bard finally publicly unveiled his project, which we now know under two names: Hedera and Hedera Hashgraph. However, not many people wonder what the key difference is. We will now explain.
Hedera + Hashgraph = Hedera Hashgraph?
The statement in the headline is correct on the one hand, but not quite on the other. Basically, we can say that Hedera Hashgraph is the name of the company. Hedera Hashraph can also refer to the private management circle that runs the company. Whereas Hashgraph is the name of the consensus algorithm that Leemon Baird worked on for many years.
Why consider Hashgraph?
- Security Hashgraph uses Asynchronous Byzantine Fault Tolerance (aBFT), a type of BFT, to secure data stored on the network. It can be said that this is one of the strongest degrees of protection presented within cryptography, allowing much less worry about security.
- Transaction Speed When it comes to speed, the Gossip protocol comes into the game. It can handle up to 10,000 transactions per second, with verification occurring instantaneously. A technical feature of the protocol is that as the number of nodes in the network increases, they increase the effective processing power of the network.
- Scalability The aspect that Dr. Limon Baird was working on. This asymmetric algorithm technology is much more scalable; the risk of bifurcations is greatly reduced.
- ACID Hashgraph is compatible with ACID (atomicity, consistency, isolation, longevity), a term that applies to databases and ensures data consistency
Is it not a blockchain?
Once again, the same fate! On the one hand true, but on the other hand not really. Hashgraph, as the developers claim, is a more efficient substitute for blockchain. In essence, they use a different way of signing blocks. Whereas blockchain uses a clear sequence, Hashgraph uses Directed Acyclic Graph (DAG). The main difference lies in the type of block recording.
To summarise briefly, we can outline Hedera with a quote from writer Rachel Hoffman:
It’s quite strange to look at the chaos and think: ‘Oh, there’s clearly a perfectionist living here’. But it’s quite typical.
Hedera really may look like chaos, with a perfectionist lurking in it. Hedera’s acyclic method promises all the benefits of blockchain but excludes low transaction speeds.
If we approach the question in the headline mathematically, we can quote a passage from the technical documentation: Asynchronous Byzantine Error Tolerance. To put it simply: in order to affect a network, more than two-thirds of the network must agree (analogous to a 51% attack requesting more capacity to make changes)
Gossip, gossip, gossip = protocol?
To circumvent the mining structure, Hashgraph uses a consensus protocol based on virtual voting. This system, in turn, is supported by its information transmission system, called the Gossip Protocol. The origin of the Gossip Protocol stems from the replication algorithms described by Demers Alan, Green Dan, Hauser Carl, Irish Wes, Larson John, Schenker Scott, Sturgis Howard, Swinhart Dunham, and Terry Doug in their study “Epidemic algorithms for a replicated database. Maintenance” dated 1987. This work is vital to the development of these algorithms, not only for Hashgraph but also for other areas of computing.
During an event, each node calls two other randomly assigned nodes. These nodes are randomly selected, and transaction details are passed to them. At the end of the event, all nodes have called each other, creating a network in which each node has a hash of the previous block. This is a tree-like system where you can visualize how the leaves connect to other leaves. The way each node connects to each other is what makes Hashgraph technology so unique and amazing at the same time.
Hashgraph transaction cycle
For a more detailed understanding, the whole Hashraph cycle needs to be deconstructed. Understandably, the process can seem quite complicated, so let’s go step by step:
↓ Network members (nodes) exchange data using the Gossip protocol
↓ The transaction data is sent to two random nodes, which are then forwarded to two more random nodes, and so on exponentially until there are enough confirmations to approve the transaction. (The system can be said to look like the Tor browser shell, with an encryption process that works in a very similar way.)
↓ Nodes begin exchanging transaction data (by the way, in a blockchain network, all information on the network is exchanged.) Along with the process, the information is not stored in blocks, but in hashes. This allows the data to be exchanged much faster.
↓ Ultimately, transactions are recorded in chronological order, allowing them to be tracked down later.
The whole transaction cycle described above is essentially a hashgraph. In a hashgraph each node knows the entire transaction history, so “virtual voting” is used to achieve consensus. No need to coordinate all the nodes among themselves: each of them already knows how the other one will “vote”. Also, as can be seen above, there is no need to use mining nodes to verify the information. This results in faster and more efficient transactions while maintaining security and reliability.
I like Hedera and I want to use it. What should I do, to begin with?
Hedera offers the user four main services:
- A cryptocurrency service
- Smart contracts service
- Storage service
- Сonsensus service. Which in turn includes a timestamped cryptography service
All third-party applications built on Hedera will have asynchronous Byzantine fault tolerance. Hedera claims that Hashgraph can host Stablecoins, financial markets, exchanges, and even real-time games. Hedera can also be used to exchange encrypted messages using short-term private keys.
The programming languages used by Hashgraph
The programming language used by Hashgraph includes LISP and Java. The core is written in these two programming languages. However, it leans towards a JVM language such as Scala, Java using the SDK offered by Hashgraph.
Hashgraph is a really interesting concept that is able to shake up the market one day. It works much faster than traditional distributed ledger technology. However, it does have its flaws. While the lack of mining has a positive impact on network speeds, for many it can be a discouraging factor. And the amount of criticism the cryptocurrency faces can have a very serious impact on its value.
In terms of technology and mathematics, Hashgraph is a seamless infrastructure with a claim to ubiquitous use and a solution to long-standing problems. In terms of value, the various speculations in the information field could shake the value of the token considerably. No one likes a competitor.