Resource Manager Scheduling for Deadline-Based Cloud Pricing
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Solution Overview
Problem
Managing dynamic pricing and resource allocation in large-scale cloud computing environments is complex, as providers must balance competing demands, ensure resource utilization, and meet customer deadlines and budgets, while clients desire flexible resource selection and cost optimization.
Innovation Solution
A resource manager system that allows clients to submit task execution queries with deadlines and budget constraints, generating execution plans that select resources from pools based on pricing policies and utilization, enabling flexible scheduling and dynamic resource allocation across availability zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the provider network operator implements flexible resource allocation and dynamic pricing, then resource utilization and revenue are improved, but the complexity of provisioning and managing physical computing resources increases
Solution Approach 1:
The patent introduces a resource manager as an intermediary system between clients and the physical computing resources. This resource manager handles the complex tasks of resource provisioning, allocation, and management, thereby improving resource utilization without increasing the operational complexity for end users. The resource manager acts as a mediator that translates client resource requests into appropriate physical resource allocations while managing pricing and utilization dynamics.
2Reliability
If long-term resource reservations are implemented, then guaranteed commitments to clients are honored, but the dynamically-varying component of resource pricing cannot be optimized
Solution Approach 1:
The patent segments resource reservations into different types: long-term reservations that guarantee commitments and short-term or spot reservations that allow dynamic pricing optimization. This segmentation enables the system to simultaneously honor guaranteed commitments for long-term clients while optimizing pricing for shorter-term needs, resolving the contradiction between reliability and pricing flexibility.
3Reliability
If the provider network operator ensures all guaranteed commitments to clients are honored, then client satisfaction is improved, but the provider's data center investment cannot be fully justified by resource utilization
Solution Approach 1:
The patent implements dynamic resource allocation where the system can flexibly assign resources based on real-time demand, pricing conditions, and client commitments. This dynamic approach allows the provider to optimize resource utilization across the data center while still honoring guaranteed commitments, as the system can dynamically adjust allocations to maximize utilization without sacrificing client promises.
Data Source
AI summary
Methods and apparatus for deadline-based pricing and scheduling of network-accessible resources are disclosed. A system includes resources organized into a plurality of pools, and a resource manager. The resource manager receives a task execution query comprising a specification of a task to be performed for the client. The specification includes the task's deadline and a budget constraint. In response, the resource manager generates a task execution plan comprising using a resource from a selected pool to perform at least part of the task, where the pool is selected based at least partly on a pricing policy of the pool. In response to an implementation request for the task, the resource manager schedules at least a part of the task using a particular resource from the selected pool.