Hashgraph is a distributed consensus algorithm and data structure designed to achieve high levels of scalability, security, and fairness in decentralized networks. It was developed by Leemon Baird and introduced in 2016. Hashgraph aims to address some of the limitations and challenges faced by traditional blockchain systems.
At its core, Hashgraph is a directed acyclic graph (DAG) data structure that records and orders transactions. Unlike traditional blockchains that rely on a linear chain of blocks, Hashgraph organizes transactions in a graph structure, which allows for parallel processing and faster transaction confirmation times.
The key principle behind Hashgraph is a consensus algorithm called “gossip about gossip” or “gossip protocol.” In this algorithm, nodes in the network communicate with each other by gossiping information about the transactions they have seen. This information includes both the transaction data and the history of communication between nodes.
By exchanging gossip, nodes gradually build a graph that represents the order and dependencies of transactions. Through a series of rounds and virtual voting, consensus is achieved on the order and validity of transactions. This consensus process is asynchronous, meaning that nodes can participate in the consensus algorithm at any time without relying on a fixed time slot.
Hashgraph also incorporates a Byzantine fault-tolerant (BFT) consensus mechanism, which ensures that the system can tolerate malicious nodes or attacks without compromising the security and correctness of the network.
Benefits of Hashgraph include high transaction throughput, low latency, fairness in transaction ordering, resistance to DDoS attacks, and strong security guarantees. However, it’s important to note that Hashgraph is a patented technology, and its implementation is subject to specific licensing terms.
Overall, Hashgraph presents an alternative approach to achieving distributed consensus and has gained attention for its potential applications in areas such as cryptocurrency, supply chain management, decentralized finance (DeFi), and more.
Here’s a simplified explanation of how Hashgraph works:
Gossip Protocol: Nodes in the network communicate with each other by gossiping information. Each node sends a message to a few randomly selected nodes, sharing the information it has about transactions and the history of communication.
Event Creation: Each node collects incoming messages and creates events. An event represents a specific action, such as a transaction or the receipt of a gossip message. Events are timestamped with the node’s local time and assigned a unique hash.
Event Ordering: Nodes use a consensus algorithm called “virtual voting” to determine the order of events. In each round, nodes exchange virtual votes that contain their preferences for the order of events. The voting process is asynchronous, allowing nodes to participate at any time.
Gossip about Gossip: In addition to gossiping about transaction information, nodes also gossip about the voting information they have received. This process is known as “gossip about gossip.” It allows nodes to build a directed acyclic graph (DAG) that represents the order and dependencies of events.
Hashgraph Data Structure: The directed acyclic graph (DAG) created through the gossip about gossip process is known as the Hashgraph. It contains the complete history of events and the voting information associated with each event.
Consensus and Finality: As nodes continue to exchange gossip, they gradually reach consensus on the order of events. Once consensus is achieved, the order of events becomes finalized, and nodes can determine the state of the network at any given point in time.
Byzantine Fault Tolerance: Hashgraph incorporates a Byzantine fault-tolerant (BFT) consensus mechanism. This means that the algorithm can tolerate a certain number of malicious or faulty nodes without compromising the security and correctness of the network.
By utilizing the gossip protocol, virtual voting, and the Hashgraph data structure, Hashgraph achieves high transaction throughput, low latency, and fairness in transaction ordering. It offers strong security guarantees and can resist various types of attacks.
