Parallelism in Blockchain Networks: How do networks process multiple transactions at the same time?

The Urgent Need for Faster Processing

Blockchain networks face a fundamental challenge: how to handle thousands of transactions per second without stopping or experiencing bottlenecks? This is where parallelism comes in as a revolutionary technical solution. Instead of processing each transaction sequentially ( one after the other ), parallelism allows the network to examine and validate multiple transactions at the same moment in time.

This approach radically changes the way blockchain operates. Instead of waiting for the second transaction to finish before processing the first, the network can handle them together, which doubles efficiency and reduces congestion.

How does parallelism work at a practical level?

When multiple transactions reach the network, blockchain nodes organize this data in an intelligent way that allows for concurrent verification. The processing task is distributed across several nodes, with each node taking on a portion of the workload instead of a single node handling everything.

During parallel processing, the network examines multiple scenarios simultaneously, with each scenario representing a different outcome for a specific set of transactions. This concurrent evaluation allows the system to see the potential impact of the transactions before they are finally recorded in the public ledger of the network. After that, all nodes agree on a unified state that reflects the overall result of these parallel operations.

Two Main Models for Parallel Execution

Optimistic Model: Fast Processing Without Pre-Examination

In this model, the network skips the initial sorting step and processes transactions directly at the same time. The basic idea here is the assumption that most transactions in the queue are independent of each other, meaning they do not affect each other.

The system uses a review and correction strategy: if it later turns out that some transactions have dependencies ( that rely on each other ), the system adjusts and reorders them. This ensures that the data remains correct and accurate even if a collision or conflict occurs.

Case Classification Model: Smart Sorting Before Execution

This model begins with an additional step: classifying transactions based on their impact on the network state. For example, the system identifies which transactions interact with specific smart contracts and which ones affect certain accounts.

Based on this classification, transactions that do not conflict with each other are executed in parallel directly. Those that affect the same elements in the network are processed in a specific order, usually according to transaction fee priorities.

Three Levels of Applying Parallelism

parallelism at the level of individual transactions

This level allows for the processing of multiple transactions simultaneously, significantly increasing the network's throughput. The network can execute a larger number of transactions per second, defined by the TPS number, and importantly, it reduces the time taken to confirm each transaction.

However, this model presents real technical challenges. Handling concurrent transactions may create complex dependencies, where the outcome of one transaction can affect another. Managing these dependencies and ensuring consistency requires advanced programming strategies.

( Parallelism at the block level

Instead of processing one transaction at a time, this mode allows for the creation and validation of multiple blocks simultaneously. The result is a more scalable network capable of preventing bottlenecks.

However, this approach requires more complex calculations and greater computing resources. Each node in the network needs higher processing power, which may limit the number of people able to run nodes securely and efficiently.

) The parallel execution of smart contracts

Decentralized blockchain applications ###DApps### benefit directly from executing multiple smart contracts simultaneously. This significantly enhances performance and speed.

Some technical solutions facilitate this pattern. For example, aggregations that use the optimistic model process transactions off the main chain and then only record the final results, which alleviates the heavy load. There are also solutions that combine advanced encryption techniques with off-chain processing, providing greater scalability while maintaining privacy.

Tangible Benefits of Parallelism

( unprecedented processing speed

Distributing tasks across multiple nodes means much shorter execution times. Networks that implement parallelism are usually faster and more efficient compared to those that follow the old sequential models.

) true scalability, not theoretical

Parallelism solves the scalability problem by distributing the transaction verification process across different nodes. This speeds up the process and supports what is called horizontal scalability, where the network can add or remove nodes based on fluctuations in demand.

actual reduction in transaction fees

Processing transactions on sub-nodes is less expensive than processing sequentially, which requires checking each node for each transaction. Additionally, the increase in transaction speed reduces competition among users for fees, leading to further cost reduction.

Current Challenges and Survey towards the Future

Despite the significant advantages, parallelism presents complex technical challenges. Ensuring that results do not conflict, maintaining network security during concurrent processing, and managing computational resources—all of this requires advanced and well-considered solutions.

The future holds promising possibilities. Integrating parallelism with other scaling solutions like sharding could open up entirely new horizons for blockchain networks, enabling them to handle massive numbers of transactions with high efficiency.