Task Throttling Based on Interactivity Levels
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Solution Overview
Problem
Existing resource allocation methods in computing environments are inefficient, particularly for interactive tasks, as they do not effectively differentiate between interactive and non-interactive tasks, leading to suboptimal resource utilization and potential service denial or crashes.
Innovation Solution
A system that includes a health framework to monitor resource health and throttle tasks based on their interactivity levels and resource usage, delaying non-interactive tasks to prioritize interactive ones, using a throttling policy that considers user identity, resource health, and task characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If resources are allocated using traditional scheduling schemes that process tasks in order received, then fairness between different tasks is maintained, but interactivity and responsiveness for user-facing tasks deteriorate
Solution Approach 1:
The patent applies local quality by differentiating resource allocation based on task characteristics. Interactive tasks receive preferential resource allocation while non-interactive tasks receive standard allocation, creating localized quality differences in resource distribution that enhance overall system responsiveness without compromising total resource utilization efficiency
Solution Approach 2:
The system dynamically adjusts resource allocation based on real-time task interactivity assessment. The resource manager continuously evaluates incoming tasks and modifies resource distribution accordingly, allowing the system to adapt between favoring interactivity and maintaining efficiency based on current workload composition
2Ease of operation
If more computing resources are allocated to improve interactivity, then responsiveness improves, but resource costs and system complexity increase
Solution Approach 1:
The system implements self-service by enabling tasks to self-identify their interactivity characteristics through metadata or classification mechanisms. This automated self-service approach reduces the complexity of manual resource allocation management while maintaining high responsiveness for interactive tasks
Solution Approach 2:
The patent applies preliminary action by pre-classifying tasks as interactive or non-interactive before resource allocation occurs. This advance classification allows the system to prepare appropriate resource allocation strategies in advance, simplifying real-time decision-making and reducing operational complexity
3Ease of operation
If all tasks are processed equally regardless of interactivity, then resource allocation simplicity is maintained, but user experience quality deteriorates
Solution Approach 1:
The patent implements local quality by applying different resource allocation policies to different task types. Interactive tasks receive enhanced resource allocation to improve user experience quality, while non-interactive tasks receive standard allocation, creating localized quality improvements where they are most needed without unnecessarily increasing overall resource consumption
Data Source
AI summary
The described implementations relate to processing of electronic data. One implementation is manifest as a system that can include logic and at least one processing device configured to execute the logic. The logic can be configured to receive a first task request to execute a first task that uses a resource when performed. The first task can have an associated first level of interactivity. The logic can also be configured to receive a second task request to execute a second task that also uses the resource when performed. The second task can have an associated second level of interactivity. The logic can also be configured to selectively throttle the first task and the second task based upon the first level of interactivity and the second level of interactivity.