Web Cluster Task Routing with Resource Matrix Feedback
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Solution Overview
Problem
Existing software complexity increases the challenge of managing and maintaining software applications, databases, and platform systems, necessitating improved resource utilization and timing in task execution, especially for computationally heavy tasks requiring fast feedback and high availability.
Innovation Solution
A computer-implemented method for distributing task execution at nodes of a web service cluster, utilizing an interface gateway to select nodes based on resource status matrices and task requirements, updating resource status matrices with real-time feedback, and optimizing resource allocation through smart routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional task distribution methods are used in web service clusters, then system simplicity is maintained, but resource utilization efficiency and task execution timing deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where service nodes continuously report their resource status (CPU usage, memory availability, load conditions) to the gateway. The gateway uses this real-time feedback to dynamically adjust task routing decisions, ensuring tasks are directed to nodes with optimal resource availability, thereby improving resource utilization efficiency while managing system complexity through structured feedback loops.
Solution Approach 2:
The system performs preliminary evaluation of node resource status before task assignment. The gateway maintains updated resource status matrices and pre-assesses node capabilities against task requirements before making routing decisions. This preliminary action ensures that tasks are assigned to suitable nodes in advance, optimizing resource utilization and execution timing without requiring complex real-time negotiations during task distribution.
2Loss of time
If dynamic task distribution is implemented, then task execution timing and resource utilization improve, but system complexity increases
Solution Approach 1:
The patent changes the parameter of task routing from static (fixed routing rules) to dynamic (resource-status-dependent routing). The gateway evaluates multiple parameters including CPU usage, memory availability, and current load on each node, and adjusts routing decisions based on these changing parameters. This enables optimized task execution timing while managing complexity through focused parameter monitoring rather than comprehensive system control.
Solution Approach 2:
The system segments the complex task distribution problem into manageable components: (1) resource status monitoring at individual nodes, (2) status matrix maintenance at the gateway, (3) task requirement analysis, and (4) routing decision generation. This segmentation allows each component to operate independently with well-defined interfaces, improving task execution timing through specialized processing while containing overall system complexity through modular architecture.
3Measurement precision
If resource status monitoring is continuously updated, then task routing accuracy improves, but information processing overhead increases
Solution Approach 1:
The patent implements partial monitoring by focusing resource status collection on critical parameters (CPU usage, memory availability, load conditions) rather than comprehensive system state tracking. Nodes report only the essential resource metrics needed for task routing decisions, and the gateway maintains selective resource status matrices. This partial action approach achieves sufficient measurement precision for accurate task routing while minimizing information processing overhead by avoiding unnecessary data collection and processing.
Data Source
AI summary
The present disclosure relates to computer-implemented methods, software, and systems for distributing task execution at nodes of a web service cluster. A request is sent from an interface gateway to execute a task at a first service node at a web service cluster. The first service node is one of a plurality of service nodes at the web service cluster. The first service node is selected to execute the task based on evaluating a resource status matrix defining resource statuses of the plurality of service nodes in the web service cluster and resource requirements of the task. A status response from the first service node is obtained after executing the task. The status response comprises a current resource snapshot of the first service node. The resource status matrix is updated based on the obtained status response from the first service node.