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    Blockchain Latency: How Confirmation Time Affects the Network

    Blockchains still have a long way from gaining mass adoption due to their complex nature, scalability problems, and high latency in some cases. Blockchain latency is the time between submitting a transaction to the network and its first confirmation. This measure can have various effects that hinder the blockchain from competing with traditional financial systems as it creates a large gap in waiting time for the end user. 

    Let’s take a deep dive into what blockchain latency is, its relationship to network throughput, and its effect on the network. 

    Blockchain Confirmation Time

    Blockchains differ from other traditional payment methods by operating on distributed peer-to-peer systems. That means, thousands of nodes confirm transactions instead of one centralized entity. By reaching a consensus, the network confirms a batch of transactions (a block) and adds it to the blockchain.  

    The time recorded between the moment a blockchain transaction is submitted to the blockchain and the time it becomes confirmed within a valid block is called confirmation time. This time frame can dictate the average speed of a blockchain network. However, confirmation time can vary depending on various factors within a network, which often would create latency issues. 

    Blockchain Confirmation Time

    So, What Is Blockchain Latency?

    Blockchain latency in this sense refers to the time delay between issuing a transaction and finalizing it. In general, latency in computing refers to the delay between input and output. The input in cryptocurrencies would be the submittal of a certain transaction and the output would be its confirmation. 

    Since the blockchain is decentral, the waiting time between transaction submittal and confirmation is longer than other methods of payment. For instance, in classical payment systems, transactions are final once the central system confirms them. 

    However, transactions on the blockchain are not confirmed immediately. In order for transactions to be final, they have to go through more than one confirmation process. After being added to the blockchain, users have to wait for other blocks to be written on top of their block. 

    Latency blockchain

    This means users have to wait until a transaction goes through various consensus-related steps and is x-blocks deep before finalization, which results in latency issues. 

    There are two types of blockchain latency within the crypto ecosystem: 

    • Network Latency: This is the time-delayed measurement of the confirmation time within the blockchain. 
    • Exchange Latency: This is the measure of an exchange’s ability to process large volumes of transactions. Exchanges that are efficient usually have low latency and high throughput that can process transactions in a consistent time frame. 

    The Effects of High Latency 

    In an extremely volatile market, having high latency is very inefficient. Cryptocurrencies’ volatile prices can fluctuate within seconds, and thus, having a long confirmation time and processing can affect traders by not taking advantage of real-time asset prices. 

    Consider the following example: You conducted a transaction with a certain currency. By the time the currency is processed and confirmed, its value increased $100. You would be paying extra cash you didn’t intend to. 

    Market Latency

    However, some take advantage of the lack of conformity between low-latency and high-latency exchanges to capitalize on the price differences as part of arbitrage trading. 

    Latency Vs. TPS 

    The throughput of a certain blockchain network is the rate at which many transactions can be confirmed within a certain timeframe. This is typically measured in transactions per second or TPS. Usually, a blockchain that “scales” at a high TPS rate is “efficient”. However, users don’t generally care about the throughput of a network. 

    What users care about is latency and transaction fees. Traders expect their transactions to be quickly finalized at the lowest fees possible. But doesn’t have a higher TPS rate increase the confirmation speed? Not exactly. In the blockchain’s timeline, having a high throughput can lead to network congestion, which again results in high latency. 

    Latency and throughput are a tradeoff that isn’t too smooth. When a network approaches its maximum TPS, an inflection point can make latency increase sharply. 

    Latency vs Throughput

    Measuring Challenges

    Measuring both latency and throughput is a tricky business. For example, where do you start measuring the latency time? When the user submits the transactions, or when the transactions hit the mempool? Does it stop when the transaction is in a valid block, or should we wait until three or six blocks get on top of it? 

    There’s also the latency of the peer-to-peer network itself and the latency of the user’s local machine to broadcast the transaction. This means that latency depends on many factors with no fixed pattern. 

    Factors that Affect Latency in a Blockchain 

    So, what are the things that affect blockchain latency?

    • Batching: Batching transactions into blocks increases the latency of a blockchain network. That’s because each transaction has to wait until the block is full before proceeding to validation. 
    • Inconsistent Congestion: Sometimes, more transactions get broadcasted to the network than it can immediately handle. The unpredictable influx of transactions depends on external market factors such as the increase in value of a token or a long-awaited NFT collection launch. 
    • Consensus Change: One blockchain‘s latency can differ from another’s by the types of consensus it operates on. 

    Is Blockchain Latency Fixable?

    Blockchains with low latency tend to be more desirable than one’s with high latency. This is valid because people don’t want to wait around 10 minutes to finalize their transactions. Latency issues can be partially solved by implementing layer-2 scaling solutions such as state channels and side chains and by layer-1 solutions such as sharding and change of consensus. Blockchains are still in their infancy and more solutions are developing for future widespread adoption.

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