Stepped Computing Resource Allocation for Queue Processing
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Solution Overview
Problem
Conventional computing resource allocation schemes in cloud environments, such as the simple linear allocation method, fail to provide flexible and efficient processing for both large and small numbers of items in a queue, leading to suboptimal resource utilization.
Innovation Solution
Implementing a stepped computing resource allocation scheme where the rate of additional resource allocation changes based on the number of items in the queue, using a list of computing resource allocation steps that define specific ranges and corresponding rates of resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a simple linear computing resource allocation formula (X/D, up to M) is used, then the allocation method is simple and easy to implement, but the resource utilization is poor and cannot efficiently accommodate both large and small queue sizes
Solution Approach 1:
The patent divides the computing resource allocation into multiple discrete steps or tiers, where each step corresponds to a specific queue size range and allocates resources at a different rate. This segmentation allows the system to apply different allocation strategies for different queue sizes, improving overall resource utilization while maintaining implementation simplicity through a structured, stepwise approach.
Solution Approach 2:
The patent implements a dynamic allocation scheme where the computing resource allocation rate changes based on the current queue size. Instead of a fixed linear formula, the system adjusts the allocation rate dynamically by selecting from multiple predefined steps, allowing efficient accommodation of both large and small queue sizes while maintaining ease of implementation through a configurable step structure.
2Speed
If D and M are lowered to allocate more computing resources for small queues, then small queues process quickly, but large queues do not receive sufficient computing resources
Solution Approach 1:
The patent applies different allocation rates (local qualities) to different queue size ranges. By defining multiple steps with different D and M values, the system can optimize for small queues in early steps while ensuring large queues receive adequate resources in later steps, resolving the contradiction between fast small queue processing and sufficient resources for large queues.
Solution Approach 2:
The patent changes the allocation parameters (D and M values) based on the queue size by selecting from multiple predefined steps. This allows the system to use different parameter sets for different queue sizes, enabling fast processing for small queues while maintaining sufficient resource allocation for large queues without requiring a single fixed parameter set.
3Quantity of substance
If D and M are raised to allocate sufficient computing resources for large queues, then large queues are well-resourced, but small queues process slowly
Solution Approach 1:
The patent segments the allocation process into multiple steps where early steps use lower D and M values optimized for small queues, while later steps use higher values for large queues. This segmentation ensures that small queues receive appropriate resources without being overwhelmed by excessive allocation, while large queues still receive sufficient resources through subsequent steps.
Solution Approach 2:
The patent dynamically selects the appropriate allocation rate based on the current queue size by evaluating which step's range the queue falls into. This dynamic approach ensures that small queues are processed with appropriate resource levels for fast completion, while large queues automatically receive higher resource allocation through the step structure, eliminating the need to choose between the two extremes.
Data Source
AI summary
A method by a computing device to allocate computing resources for processing items in a queue using a list of computing resource allocation steps. The method includes determining a total amount of computing resources that are to be allocated for processing items in the queue based on a current number of items in the queue and the list of computing resource allocation steps, where the list of computing resource allocation steps specifies a plurality of ordered steps. Each step in the plurality of ordered steps defines a rate at which additional computing resources are allocated for processing items in the queue when the number of items in the queue is within a particular range. The method further includes adjusting an amount of computing resources allocated for processing items in the queue to match the determined total amount.