Demand Forecasting Service for Virtual Computing Resources
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Solution Overview
Problem
Computing service providers face challenges in efficiently managing demand for virtual computing resources, particularly in allocating physical resources to meet both targeted and untargeted demands across different availability zones, which can lead to increased costs and resource inefficiencies.
Innovation Solution
A demand forecasting service that analyzes historical data to distinguish between targeted and untargeted demand, builds forecasting models to predict future demand, and strategically allocates physical computing resources among zones, optimizing resource utilization and cost management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical computing resources are allocated to meet user demands across availability zones, then service coverage and reliability are improved, but resource allocation efficiency and cost management deteriorate due to difficulty in distinguishing targeted versus untargeted demand
Solution Approach 1:
The patent segments user demand into two distinct categories: targeted demand (requests specifying a particular availability zone) and untargeted demand (requests without zone specification). This segmentation is achieved through the demand forecasting service that analyzes historical data and distinguishes between these demand types. By separating the demand categories, the system can apply different allocation strategies - directing targeted demand to specific zones and routing untargeted demand to zones with available resources, thereby improving resource allocation efficiency while maintaining service coverage.
2Quantity of substance
If computing service providers build additional server rooms and add more racks of servers to meet increasing user demands, then capacity and service ability are improved, but operational expenses and resource utilization efficiency worsen
Solution Approach 1:
The patent implements preliminary action through demand forecasting. The demand forecasting service analyzes historical demand data to predict future targeted and untargeted demand patterns before actual demand occurs. This prediction enables the computing service provider to proactively allocate physical computing resources in advance, building capacity only where and when needed. By taking preliminary forecasting action, the system avoids over-provisioning resources, thereby increasing capacity efficiently while controlling operational expenses through data-driven resource planning.
3Adaptability or versatility
If physical computing resources are dynamically adjusted and allocated across availability zones, then adaptability to user demands is improved, but system complexity and management difficulty worsen
Solution Approach 1:
The patent implements feedback mechanisms through the demand forecasting service that continuously monitors and analyzes historical demand data across availability zones. The service provides feedback on predicted targeted and untargeted demand patterns, enabling dynamic adjustment of resource allocation strategies. This feedback loop simplifies management by replacing complex manual monitoring and decision-making with an automated system that processes historical data and generates actionable insights, thereby maintaining high adaptability to user demands while reducing management complexity.
Data Source
AI summary
Systems and methods for managing demand for virtual computing resources are disclosed. A demand forecasting service can obtain and analyze historical demand data for purposes of predicting future demand. The analysis includes identifying untargeted demand corresponding to requests for virtual machine instances that can be fulfilled by any availability zone of a set of zones. The demand forecasting service may provide predictions of future demand including information regarding future untargeted demand, thereby enabling efficient allocation of computing resources among various availability zones to meet the future demand.