Blockchain Consensus Node Database Layer for Cache Pressure
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Solution Overview
Problem
Existing blockchain technologies face low service execution efficiency due to cache capacity limitations in consensus nodes, leading to difficulties in processing service requests and consensus verification.
Innovation Solution
Implementing a blockchain service handling method where consensus nodes include a first application, a second application, and a database, allowing service data to be stored in the database instead of cache, reducing cache pressure and enabling efficient data transfer between nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service data is stored in cache of consensus node, then consensus verification can be performed, but cache capacity is limited and service execution efficiency is low
Solution Approach 1:
The patent transitions from a single-dimension storage approach (cache only) to a two-dimension storage architecture by introducing a database layer alongside the cache. This dimensional expansion allows service data to be persisted in the database while maintaining hot data in cache, thereby overcoming the cache capacity limitation and improving service execution efficiency without being constrained by finite cache space.
Solution Approach 2:
The patent implements a nested storage structure where the database is embedded within the consensus node architecture, and the cache is nested within the database layer. Service data flows through multiple nested layers: from the application layer to the database layer for persistent storage, and selectively to the cache layer for fast access during consensus verification. This nested arrangement allows the system to leverage both the large capacity of the database and the fast access of the cache simultaneously.
2Productivity
If more service data is stored to increase processing capacity, then more services can be handled, but cache space becomes insufficient
Solution Approach 1:
The patent extracts the persistent storage function from the cache system and places it in a separate database layer. The cache is taken out from being the sole storage mechanism and is instead positioned as a supplemental fast-access layer. This extraction allows the system to store large volumes of service data in the database without being constrained by cache space, thereby increasing the number of services that can be processed per unit time.
Solution Approach 2:
The patent segments the storage system into two distinct functional layers: a database layer for persistent storage of all service data, and a cache layer for temporary storage of frequently accessed data needed for consensus verification. This segmentation allows each layer to be optimized independently - the database for capacity and the cache for speed - thereby enabling the system to handle more services without cache space becoming a bottleneck.
3Productivity
If cache occupancy is increased to improve verification efficiency, then consensus verification can proceed, but available cache for new service requests decreases
Solution Approach 1:
The patent performs preliminary action by pre-storing service data in the database before it is needed for consensus verification. This advance preparation ensures that when consensus verification needs to occur, the required data is already available in the database and can be quickly transferred to cache if needed. This preliminary storage action in the database eliminates the need to compete for cache space with new service requests, as the database serves as a pre-prepared reservoir of verification data.
Solution Approach 2:
The patent introduces the database as an intermediary layer between service request intake and consensus verification processes. When service data arrives, it is stored in the database intermediary layer. When consensus verification is needed, data is retrieved from this intermediary layer and transferred to cache. This intermediary database buffer decouples the cache occupancy from new service request processing, allowing the system to maintain high verification efficiency while remaining adaptable to new requests.
Data Source
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AI summary
The present application discloses a blockchain service acceptance and consensus method and apparatus. A consensus node includes a first application, a second application, and a database, and the database is configured to store service data obtained after the first application and the second application perform processing, to reduce cache pressure of the consensus node. It can be seen that, by using the methods provided in the implementations of the present application, provided that the consensus node determines service data corresponding to the service request, the consensus node can store the service data in the database, and wait to send the service data to another consensus node, and therefore, a cache occupancy rate of the consensus node is relatively low. Therefore, the number of services that can be processed by the consensus node in unit time is increased, and consensus verification efficiency and service request processing efficiency of the consensus node are improved.