Coordination Server Load Balancing for Blockchain Data Processing
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Solution Overview
Problem
The frequent read/write operations by service servers on blockchain servers cause significant access pressure, leading to decreased data processing speed in existing data processing systems.
Innovation Solution
A data processing method and apparatus that select a target coordination server based on performance information of server clusters to prioritize data processing requests, allowing for load balancing and accelerated data processing by routing requests to server clusters with higher capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service servers perform frequent read/write operations on blockchain servers, then data processing functionality is maintained, but access pressure increases and data processing speed decreases
Solution Approach 1:
The patent introduces coordination servers as intermediaries between service servers and blockchain servers. These coordination servers receive data processing requests from service servers, select appropriate blockchain servers based on load and performance information, and forward requests accordingly. This intermediary layer distributes access pressure across multiple blockchain servers and optimizes request routing, thereby reducing the burden on individual blockchain servers while maintaining data processing functionality.
Solution Approach 2:
The system segments the blockchain network into multiple server clusters, each with its own coordination server and blockchain servers. By dividing the monolithic blockchain server into distributed clusters, the patent enables parallel processing of requests and distributes access pressure across multiple independent units. Each cluster can handle requests independently, improving overall system throughput and reducing congestion on any single server.
2Productivity
If multiple coordination servers are used for load distribution, then data processing speed improves, but system complexity increases
Solution Approach 1:
The patent implements load balancing mechanisms that maintain equipotentiality across multiple coordination servers by continuously monitoring and comparing performance information from different server clusters. The coordination servers use consistent selection criteria based on real-time load metrics, ensuring that requests are distributed evenly and optimally across clusters. This standardized approach simplifies the management of multiple coordination servers by providing a uniform decision-making framework.
Solution Approach 2:
The system incorporates feedback loops where coordination servers continuously collect performance information from blockchain servers, analyze current system state, and dynamically adjust request routing decisions. This feedback mechanism enables the system to adapt to changing conditions automatically, optimizing data processing speed while managing complexity through intelligent, adaptive control rather than static configuration.
Data Source
AI summary
A data processing computer-implemented method, medium, and system are disclosed. In one computer-implemented method, a target coordination server is selected from multiple coordination servers based on performance information of server clusters, where the multiple coordination servers respectively belong to multiple server clusters. A data processing request is sent to the target coordination server, so that a server cluster that the target coordination server belongs to can prioritize handling of the data processing request.