Distributed Task Scheduling with Independent Databases for High Availability

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Solution Overview

Problem

In SaaS environments, existing task scheduling systems face issues with databases becoming single bottlenecks, leading to performance decline and inoperability when the load increases, which is not effectively addressed by current high availability and scalability methods.

Innovation Solution

A distributed scheduling system with a master scheduling platform and multiple slave platforms, where scheduling data maintenance is distributed across these platforms, allowing them to execute tasks independently and maintain high availability by using independent databases.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If a centralized database is used for task scheduling, then the system structure is simple, but the database becomes a single bottleneck point and cannot handle large loads

Engineering Contradiction:

Improvesystem structureVSAvoidscheduling task handling capacity

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The patent divides the centralized database into multiple distributed databases, with each slave scheduling platform having its own independent database. This segmentation allows the system to handle larger loads by distributing tasks across multiple database instances, eliminating the single bottleneck point while maintaining manageable system structure through modular design.

Inventive Principle:

Principle #1Segmentation

2Device complexity

If a centralized database is used for task scheduling, then the system structure is simple, but the database becomes a single point of failure

Engineering Contradiction:

Improvesystem structureVSAvoidsystem availability

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The patent segments the centralized database into multiple distributed databases associated with different slave scheduling platforms. This segmentation ensures that failure of one database does not affect the entire system, as other databases continue to operate independently, thereby eliminating the single point of failure while keeping the overall system structure relatively simple through standardized modular components.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the database architecture parameter from centralized to distributed, and from single-instance to multi-instance. This parameter change transforms the system from having a single point of failure to having multiple redundant data storage points, significantly improving reliability and availability while maintaining manageable complexity through consistent architectural patterns.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If the number of scheduling tasks is increased, then the system functionality is improved, but the database performance declines

Engineering Contradiction:

Improvescheduling task quantityVSAvoiddatabase performance

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent segments the database workload by distributing scheduling tasks across multiple slave scheduling platforms, each with its own database. This segmentation allows the system to handle increased numbers of scheduling tasks by parallelizing database operations across multiple instances, thereby improving both adaptability to task quantity increases and maintaining database performance through distributed load handling.

Inventive Principle:

Principle #1Segmentation

4Reliability

If a distributed scheduling framework is used, then high availability in running phase is achieved, but the database still becomes a bottleneck

Engineering Contradiction:

Improverunning phase availabilityVSAvoiddatabase architecture

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the database architecture into multiple independent database instances, each associated with a slave scheduling platform. This segmentation extends the distributed architecture from the application layer to the data layer, ensuring that the database does not become a bottleneck even when the number of scheduling tasks increases, while maintaining high availability in the running phase through redundant data storage and distributed query processing.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS12566630B2Distributed scheduling system and distributed scheduling method with independent databases to prevent single point failure

Publication Date: 2026.03.03 DIGIWIN CO LTD

AI summary

A distributed scheduling system includes a master scheduling platform and a slave scheduling platform. The number of the master scheduling platform and the number of the slave scheduling platform may be dynamically expanded respectively. When a back-end operating platform provides a scheduling data maintenance request to the master scheduling platform, the master scheduling platform provides scheduling data maintenance information to the slave scheduling platform according to the scheduling data maintenance request, so that the slave scheduling platform performs maintenance on scheduling data according to the scheduling data maintenance information. When a scheduling task execution condition of the scheduling data is met, the slave scheduling platform initiates a task, and calls a corresponding micro service to execute a business logic of the scheduling data. The distributed scheduling system and a distributed scheduling method realize highly available distributed scheduling functions.