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Blockchain technology has undoubtedly transformed many industries, but the quest for true scalability remains a critical challenge. As the adoption of Web3 applications continues to increase, the need for blockchain networks capable of scaling to sustain mainstream adoption has become paramount.
Sharding emerges as a promising solution to address the scalability bottlenecks existing blockchains face, and the various approaches to sharding hold significant implications for the future of decentralized networks.
What is sharding?
At its core, sharding is a technique that partitions a blockchain network into smaller, more manageable segments known as “shards.” Each shard maintains a distinct subset of the blockchain’s data and in certain architectures, is responsible for processing a specific set of transactions. This parallel processing capability directly translates to increased network throughput, making sharding a crucial component in the quest for scalable and efficient blockchain architectures.
However, the implementation of sharding is more than just a one-size-fits-all solution. Blockchain projects have explored various sharding approaches, each with its advantages and trade-offs. Transaction sharding, network sharding, and state sharding represent the primary types of sharding, each offering unique benefits and presenting distinct technical challenges.
Types of Sharding
Compute Sharding: This approach focuses on dividing the workload based on transactions. A block of transactions is validated by a single shard and the receipt is sent to all nodes in the network. Different shards validate different blocks of transactions. All nodes store the complete network state and update the local state using the validated blocks. It’s efficient for networks with a high volume of unrelated transactions.
However, transactions involving multiple shards become complex, requiring additional communication and validation steps. Every validator stores the global state resulting in IO bottlenecks and vertical scaling storage requirements due to state bloat.
Network Sharding: This is also referred to as functional sharding. The validators are assigned to different subnets with a hub network managing the communications between the subnets. Transactions are routed to the appropriate subnet and all nodes in the subnet validate every transaction and hold the complete state. This approach distributes the computational load across different validator sets, enhancing scalability. However, it introduces challenges in maintaining global consensus and ensuring the security of the entire network.
State Sharding: Considered the most complex type, state sharding divides the address space across different shards. For example, Shard A may host addresses 0-100, Shard B hosts addresses 101 – 200, and so on. Each shard maintains its own state, offering the highest potential for scalability. However, it also presents significant technical hurdles when transactions involve accounts hosted on several shards and when additional shards need to be added to the network.
Transactions that touch several shards must be processed sequentially by each shard which hosts an account involved in the transaction. For example, in a transaction where Shard A hosts Account 1, Shard B hosts Account 2, and Shard C hosts Account 3, Shard A must first process the transaction with the data it has for Account 1, it will then forward the transaction and receipt to Shard B with the data for Account 1, Shard B will process the transaction with the data it has for Account 2, it will then forward the transaction and receipts to Shard C with the data for Accounts 1 and 2, Shard C will then complete transaction processing for Account 3 and roll back the fully processed transaction and receipts to Shards A and B so they can verify the fully processed transaction.
The sequential transaction processing state-shared blockchains must utilize in cross-shard transactions breaks atomic composability causing a challenging developer experience. Developers building on existing state-shared blockchains must think about the shard they’re deploying to if their application requires atomic composability with other contracts. As you can see robust validation mechanisms must be implemented in state-shared networks to ensure consistency across shards and prevent inconsistencies in the overall blockchain state.
Another challenge existing state-shared blockchains face is adding shards to increase throughput capacity and prevent network congestion. Developers of state-sharded blockchains must monitor the network, determine when is the right time to add a shard and implement code to add a new shard to the network. State-sharded blockchains have stepwise scalability as transaction throughput only increases when a shard size amount of nodes is added to the network.
Dynamic State Sharding: Dynamic state sharding represents the pinnacle of sharding techniques, enabling every validator node to host a unique range of address space and form a shard dynamically specific to each transaction. Unlike static sharding, where nodes within a shard share the same address range, dynamic sharding allows for a more granular distribution of workload and resources across every validator node in the network.
Specifically, the network scales linearly with each validator added to the network, as every validator hosts a unique address space and only processes transactions involving the accounts it hosts. This approach is crucial for achieving true linear scalability, as every validator added to the network immediately contributes to parallelism and reduces the overhead of other validators.
Additionally, dynamic state sharding enables blockchains to retain the atomicity of transaction consensus even when transactions involve accounts hosted by different validators. With dynamic state sharding every transaction is processed independently and routed only to the validators assigned to the accounts involved. The validators which host the accounts involved in a transaction are known as the transaction group. 128 validators from the transaction group form a dynamic shard, known as the consensus group, and vote on the transaction to achieve a quorum. As the consensus group makes up the complete transaction state consensus is achieved atomically. Developers have the same atomic composability capabilities on a dynamic state-shared network that they do on an unshared network.
Finally, dynamic state sharding brings the autoscaling UX from cloud services to web3. Validators share their CPU load and the median CPU load is used to predict the desired number of validators needed to sustain network load and prevent congestion. Validators can be rotated between a standby and active pool to adapt the network size to the desired active validator count while keeping all excess validators on standby ensuring validators are available to increase the network size when necessary. Using an autoscaling protocol, dynamic state-sharded networks can adapt throughput capacity to network load autonomously without developer involvement.
While sharding is a well-known concept, it’s the innovative applications and dynamic approaches that truly set apart the next generation of blockchain networks. Leveraging predictive analytics and historical data, these advanced sharding techniques proactively distribute the load across shards, anticipating future congestion and optimizing resource utilization. This ensures optimal performance during periods of high demand and enables true linear scalability, where the introduction of new nodes instantly boosts the network’s transaction throughput.
Challenges
The challenges of sharding are not to be underestimated, requiring robust validation mechanisms to ensure consistency across shards and prevent inconsistencies in the overall blockchain state. Maintaining atomicity and cross-shard composability, ensuring security against shard-specific attacks, and providing a seamless developer experience are just a few of the obstacles that blockchain projects are actively addressing through innovative solutions and robust security measures.
Conclusion
As the blockchain industry continues to evolve, the refinement and deployment of sharding techniques will be crucial in unlocking the true scalability of decentralized networks. By embracing advanced sharding approaches that leverage predictive analytics and dynamic load balancing, blockchain projects can position themselves at the forefront of the scalability revolution, empowering the next generation of decentralized applications and driving mainstream adoption of this transformative technology.
Through a commitment to innovation and a deep understanding of the challenges posed by scalability, blockchain projects are paving the way for a future where decentralized networks can seamlessly handle the demands of a global user base. This evolution in blockchain sharding, particularly with dynamic state sharding, represents a significant step forward in unlocking the full potential of decentralized applications and ushering in a new era of scalable and efficient blockchain architectures.