Practical Solutions for DLT Scalability
Enhancing DLT Scalability with Dynamic Sharding
DLT, such as blockchain, is crucial for managing numerous micro-transactions in the Machine Economy. To enhance DLT scalability, sharding is often used, dividing the network into multiple committees. Solutions to improve DLT scalability include first-layer approaches like sharding and bigger blocks and second-layer approaches like parallel side chains. Researchers at Luleå University of Technology propose ScaleGraph, a scalable distributed ledger method that uses dynamic sharding based on routing and logical proximity concepts from distributed hash tables. ScaleGraph enhances cybersecurity and supports frequent micro-transactions between autonomous devices.
Value of ScaleGraph
ScaleGraph’s storage complexity is O(t), sharded over n nodes, with each node needing O(t/n) storage. This method improves concurrency and data localization, offering better scalability and performance than consensus models. In ScaleGraph, a node can simultaneously act as a leader for multiple sender accounts without issues, as they involve separate chains. Unlike typical methods, ScaleGraph allows overlapping shards for increased parallelism. Simulations show that a synchronous consensus protocol significantly reduces shard size requirements compared to asynchronous ones, enhancing performance and security.
Security and Practical Considerations
To prevent double spending and ensure fault tolerance, rigorous vote counting, and periodic shard rebuilding are crucial. Sharding also reduces data redundancy, affecting availability. Future work includes a formal security analysis, more accurate failure probability modeling, and performance evaluation to balance the trade-off between shard size and system efficiency.
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