2.3. The Local Blockchain

The Eigenvector Centrality computation is expensive. As the network grows, the time complexity of this problem increases, posing scalability challenges.

We discuss how this problem is addressed and introduce solutions for common scalability, flexibility, and interoperability challenges faced by existing blockchains; combining the best features of integrated architectures with the expressivity of more modular ecosystems.

Hierarchical Sharding#

Most importantly, our approach uses a "bottoms-up" hierarchical sharding technique. The network is naturally divided into partitions called shards, each responsible for processing transactions and maintaining their local state. These shards are organized into a hierarchical structure, with higher-level shards (domaingraphs) coordinating the activities of lower-level shards (subgraphs). Domaingraphs represent custom environoments (similar to app chains) that together communicate to achieve global state (supergraph).

Local Customizability#

We allow domaingraphs to develop customized trust models (see proofs) within their respective operating environments. This flexibility accommodates the varied requirements of heterogeneous commercial settings while providing users with the right to self-custody.

Global Assets#

Assets exist on the supergraph level, eliminating the need for independent implementations in each domaingraph. Users maintain self-custody and can easily move assets between domaingraphs without the need for complex bridging mechanisms, streamlining the user experience.

Separation of Concerns#

We separate execution and transaction ordering from data availability and settlement. This allows for greater flexibility where each domaingraph has full control over its blockspace and runtime environments.

Interoperability#

The supergraph facilitates communication and coordination between domaingraphs, ensuring global state consistency. This enables seamless interoperability between different environments within the ecosystem, eliminating the fragmentation risks associated with modular architectures.

Next Steps#

In the next sections, we'll explore the technical aspects of this sharding technique and introduce the basic computational paradigm for calculating relative EC rankings in a distributed systems context.