@APRO Oracle introduces a Two-Layer Network (TLN) design to tackle the scalability bottlenecks commonly faced by traditional oracle systems. The approach decouples data ingestion and validation from end-client query throughput, enabling higher performance, improved fault tolerance, and more flexible data governance. Here’s a detailed breakdown of what the Two-Layer Network is and how it solves key scalability problems.
Core Concept
At a high level, the TLN architecture separates oracle functions into two distinct layers:
1. Layer 1 — Data Federation and Validation Layer
This layer aggregates data from multiple independent data sources, validators, and stakers.
It focuses on data truthfulness, freshness, and integrity, providing a robust, cross-verified data feed.
Validations and consensus-based checks occur here, reducing reliance on any single data source.
2. Layer 2 — Query and Delivery Layer
This layer handles end-user requests from smart contracts and off-chain clients.
It provides high-throughput querying, low-latency responses, and efficient data delivery mechanisms.
It leverages the validated data from Layer 1 to respond accurately and securely.
The two layers interact through well-defined interfaces, enabling parallelism: data validation can scale independently of query processing.
How TLN Addresses Scalability Issues
Traditional on-chain oracles often face several scalability challenges, such as single-point bottlenecks, limited throughput, and higher latency. TLN mitigates these problems in the following ways:
1) Decoupled Data Validation from Query Load
Traditional systems tie data accuracy and throughput to a single processing path. TLN decouples validation from delivery, allowing each layer to scale horizontally.
This separation means the validation layer can continuously ingest and validate data from many sources, while the query layer serves numerous consumers without being blocked by validation tasks.
2) Parallelism and Independent Scaling
Layer 1 can add more validators, data sources, and consensus instances without forcing changes in Layer 2’s query pipelines.
Layer 2 can scale its endpoint capacity (e.g., more gateway nodes, parallelized responses) while relying on Layer 1’s validated data, enabling higher aggregate throughput.
3) Improved Data Freshness and Reliability
By aggregating multiple trustworthy sources and applying cross-source validation, the system reduces reliance on any single oracle and mitigates data staleness.
A layered approach enables more frequent updates in Layer 1 without overwhelming the end-user delivery path in Layer 2.
4) Fault Tolerance and Privacy Controls
Layer 1’s distributed validation provides resilience against data source failures or manipulation attempts. If one validator behaves maliciously or goes offline, others continue to operate.
Layer 2 can implement rate-limiting, access controls, and privacy-preserving data delivery, ensuring secure and scalable client interactions.
5) Modularity and Ecosystem Growth
New data feeds or validation mechanisms can be added to Layer 1 with minimal impact on Layer 2’s interfaces.
This modularity supports ecosystem growth, enabling practitioners to integrate diverse data kinds and provenance schemes without redesigning the oracle’s core delivery path.
Typical Data and Interaction Flow
A simplified workflow in the TLN model might look like this:
1. Data arrives from multiple sources into Layer 1.
2. Validators perform cross-checks, consensus, and cryptographic proofs to establish a trusted state.
3. The validated result is published or anchored to a Layer 1 state, accessible to Layer 2.
4. Applications submit queries to Layer 2.
5. Layer 2 retrieves the validated data from Layer 1, computes any necessary local logic, and returns a response to the requester.
6. Optional proofs or attestations are delivered to users or smart contracts to verify the data’s integrity.
Trade-offs and Considerations
Latency vs. Throughput: The additional validation step can introduce slightly more latency than a single-source oracle, but it yields higher trust and resilience, enabling sustainable high throughput at scale.
Complexity: The two-layer approach introduces more architectural components. Operational excellence, monitoring, and clear interfaces are essential to avoid fragmentation.
Governance: Layer 1’s multi-source validation requires governance for source selection, validator incentives, and dispute resolution mechanisms to maintain data quality.
Why Two Layers Are Beneficial in Practice
By enabling independent scaling paths, TLN supports growing data ecosystems where multiple data streams must be ingested and validated continuously while the demand for fast, reliable contract calls remains high.
The architecture aligns with the broader trend in decentralized systems toward modularity, where data provenance, validation, and delivery are handled by specialized subsystems that can evolve at different cadences.
Conclusion
APRO’s Two-Layer Network offers a structured approach to scaling oracle infrastructure by decoupling data validation from data delivery. This separation:
Improves throughput and resilience through parallelism,
Enhances data integrity via multi-source validation,
Provides flexible governance and easier ecosystem expansion.
The TLN design aims to address the core scalability pain points of traditional oracle systems while preserving trust, verifiability, and low-latency delivery for smart contracts and off-chain consumers.
