1. Scalability Constraints on the Base Layer

Layer 1 scalability is constrained by:

• Bandwidth: the rate at which nodes can exchange blocks and transactions.
• Latency: network propagation time for block dissemination.
• Computation: cost of verifying signatures and executing transactions.
• Storage: long-term state growth and archival requirements.

Simply increasing block size or frequency can overwhelm less capable nodes, contributing to centralisation.

2. Sharding Fundamentals

Sharding partitions the blockchain’s workload across multiple subsets of nodes (shards):

• Each shard processes its own transactions and maintains a partial state.
• No single node needs to validate all transactions in the system.
• Throughput scales approximately with the number of shards, subject to cross-shard overheads.

Key design challenges include cross-shard communication, security against shard takeovers, and data availability.

3. Cross-Shard Communication and Atomicity

Transactions often involve multiple shards. Mechanisms for cross-shard operations include:

• Asynchronous message passing with acknowledgements.
• Receipt-based protocols referencing proofs of inclusion.
• Atomic commit schemes (e.g., two-phase commit variants adapted to BFT settings).

Designs must ensure:

• No double spending across shards.
• Eventual consistency of state transitions.
• Practical latency for user operations.

4. Shard Security, Randomness and Validator Assignment

Sharding introduces the risk that adversaries may concentrate power in a single shard. Mitigations include:

• Random assignment of validators to shards.
• Frequent reshuffling to reduce attack windows.
• Using global consensus mechanisms to confirm shard outputs.

Verifiable random functions (VRFs) and randomness beacons play an important role in unpredictable committee selection.

5. Data Availability and Sampling Techniques

As blocks grow or shard outputs are aggregated, verifying data availability becomes critical. Data availability sampling (DAS) allows light nodes to probabilistically verify that data is widely available without downloading it entirely.

• Blocks are erasure-coded into many pieces.
• Light clients randomly sample shares.
• If enough random samples are retrievable, it is highly likely the full data is available.

6. DAG-based Ledger Architectures

Instead of a single chain, some protocols use a Directed Acyclic Graph (DAG) of blocks or transactions:

• Multiple blocks can be produced concurrently.
• Edges capture references or ordering constraints.
• Consensus defines how to extract a linear history from the DAG.

DAG-based approaches aim to increase throughput while maintaining eventual agreement on a total order or partial order sufficient for application semantics.

7. Block Propagation Optimisations

Efficient block propagation reduces fork rates and enables larger blocks. Techniques include:

• Compact blocks: sending transaction IDs instead of full transactions when peers already have mempool entries.
• Graphene and similar schemes: compressed set reconciliation.
• Relay networks: specialised low-latency infrastructure for rapid block distribution.

8. State Pruning, Stateless Clients and Witnesses

As on-chain state grows, full nodes face increasing storage burden. Stateless client concepts propose:

• Storing minimal persistent state at nodes.
• Providing state witnesses (Merkle/Verkle proofs) with each transaction.
• Allowing validators to verify state transitions using proofs rather than local full state.

This shifts storage load towards those who submit transactions or maintain specialised state services.

9. Trade-offs Across Layer 1 Scalability Techniques

All Layer 1 scalability techniques face trade-offs among:

• Throughput and latency.
• Validator resource requirements.
• Security assumptions (e.g., honest majority per shard vs system-wide).
• Complexity of protocol implementation and analysis.

Effective designs carefully balance these factors to avoid creating new attack surfaces or centralisation pressures.

10. Module Summary

This module reviewed major Layer 1 scalability strategies: sharding, DAG-based ledgers, data availability sampling, and propagation optimisations. We highlighted the interplay between security assumptions, validator requirements, and user-facing performance metrics.

In Module 5, we extend our focus to Layer 2 scalability—payment channels, rollups, sidechains, bridges, and cross-chain interoperability—completing the systems-level picture of blockchain scalability.