Distributed Database Loading with Load Monitor Servers
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Solution Overview
Problem
Existing online information retrieval systems are vulnerable to server malfunctions during the loading of new documents, leading to delays and the need for reloading entire data sets, especially for time-sensitive information.
Innovation Solution
A distributed load domain system with multiple load servers and load monitor servers that monitor each other's performance, using a service-level-agreement (SLA) data structure to manage loading tasks and ensure redundancy, with a shared directory for communication and a load queue for workflow management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single large server is used for loading documents, then the system has simpler architecture and easier management, but the system becomes vulnerable to server malfunctions and crashes during loading process
Solution Approach 1:
The patent divides the loading system into multiple independent load servers (at least two) that work in parallel. Each load server can independently handle loading tasks, so if one server fails, others continue operating. This segmentation eliminates the single point of failure inherent in using a single large server while maintaining manageable system architecture through modular design.
2Reliability
If multiple load servers are deployed for redundancy, then system reliability improves, but coordination and monitoring complexity increases
Solution Approach 1:
The patent introduces a load monitor server that consolidates the monitoring function for all load servers into a single centralized component. This monitor server tracks the status, performance, and health of multiple load servers, coordinating their operations and detecting failures. By merging monitoring functions, the system avoids the complexity of each server monitoring itself or mutual peer-to-peer monitoring, while still achieving high availability through the redundant load servers.
3Productivity
If a single server handles all loading tasks, then resource utilization is simpler to manage, but the system experiences delays and requires reloading entire data sets upon server failure
Solution Approach 1:
The patent segments the loading workload across multiple load servers that operate simultaneously. Each server handles a portion of the loading tasks, enabling parallel processing of document loads. This division allows the system to maintain high productivity during normal operation and, crucially, to continue loading operations with remaining servers if one fails, thereby eliminating the need to reload entire data sets and reducing downtime significantly.
Solution Approach 2:
The patent implements dynamic load balancing and task distribution parameters that allow the system to adapt to server availability. When servers are healthy, the system utilizes all available servers for maximum loading speed. When a server fails, the system dynamically reassigns its workload to remaining servers, maintaining optimal productivity levels and minimizing the impact of failures on overall loading performance.
4Reliability
If load monitoring is distributed across all servers, then system reliability is improved through mutual monitoring, but communication overhead and complexity increase
Solution Approach 1:
The patent introduces a load monitor server as an intermediary component that centralizes the fault detection and monitoring function. Instead of having load servers communicate extensively with each other for mutual monitoring (which would create high communication overhead), the monitor server acts as a mediator that receives status reports from all load servers and coordinates fault detection. This intermediary approach maintains reliable fault detection capability while significantly reducing the communication overhead and complexity associated with distributed mutual monitoring.
Data Source
AI summary
The present inventors have devised one or more systems, methods, and software for distributed loading of information retrieval systems. One exemplary system includes two or more (at least two) load monitor servers that not only monitor and ensure completion of load tasks by individual load servers in a set of two or more load servers, but also provide for one load monitor to monitor performance of the another. Moreover, the exemplary system provides a service-level-agreement (SLA) data structure for each load server. The SLA data structure governs what types and priority levels of loading tasks will be performed for predetermined time periods.