Cloud Resource Allocation via Consumption Relationship Mapping
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Solution Overview
Problem
Cloud service providers face challenges in efficiently allocating resources to applications to meet quality of service (QoS) targets, leading to issues of over- and under-allocation, which can result in increased costs and failure to meet service level agreements (SLAs).
Innovation Solution
A method and system for cloud resource allocation that involves receiving data on the relationship between consumption of one resource type and another, determining the consumption level of the first resource type, and allocating resources of the second type based on this relationship, using customer preference data structures that include QoS metrics and rules to optimize resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud service providers increase resource allocation to meet QoS targets, then service reliability is improved, but resource waste and operational costs increase
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring application performance metrics and adjusting resource allocation in real-time based on actual consumption patterns and QoS requirements, rather than using static over-provisioning strategies
Solution Approach 2:
The system employs feedback mechanisms where performance data from applications is collected, analyzed, and used to adjust resource allocation decisions, creating a closed-loop control system that optimizes resource distribution based on actual needs
2Productivity
If cloud service providers decrease resource allocation to reduce costs, then operational efficiency is improved, but QoS compliance and service reliability deteriorate
Solution Approach 1:
The system performs preliminary analysis of resource consumption patterns and performance requirements to predict optimal allocation levels before making allocation decisions, preventing both over-allocation and under-allocation
Solution Approach 2:
The patent changes allocation parameters dynamically based on monitored performance metrics and consumption patterns, adjusting resource allocation levels to maintain QoS compliance while optimizing operational efficiency
3Device complexity
If cloud service providers use simple resource allocation rules, then system complexity is reduced, but resource utilization precision and QoS optimization deteriorate
Solution Approach 1:
The patent segments resource allocation into distinct controllable parameters (CPU, memory, storage, network) that can be independently monitored and adjusted, allowing complex optimization without overwhelming system complexity
Solution Approach 2:
The system implements a universal resource allocation framework that handles multiple resource types and application scenarios through a common set of principles and mechanisms, reducing overall system complexity while maintaining precision
Data Source
AI summary
A computer-implemented method of allocating cloud resources is provided that comprises: receiving, by a cloud host, data that identifies, for an application, a relationship between consumption of a first resource type and consumption of a second resource type; determining, by the cloud host, a consumption level of the first resource type of the application; and allocating, by the cloud host, one or more resources of the second resource type based on the identified relationship.