Flexible Location Resource Reservation Heuristics
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Solution Overview
Problem
Managing large-scale computing resources in data centers is complicated due to increased scale and scope, with existing virtualization technologies not effectively balancing resource allocation and pricing fluctuations, leading to challenges in ensuring client satisfaction and resource utilization.
Innovation Solution
Implementing a resource manager with a flexible location option that allows clients to specify or allow the manager to select locations for resource reservations, using heuristics for location choice based on resource utilization and availability, and offering pricing incentives for location flexibility and transferability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtualization technologies are used to share computing resources among multiple customers, then resource utilization efficiency is improved, but managing large-scale computing resources becomes increasingly complicated
Solution Approach 1:
The patent introduces a resource manager as an intermediary component that handles the complexity of managing virtualized computing resources. The resource manager sits between the virtualization layer and customers, providing simplified interfaces for resource reservation, monitoring, and allocation while handling the complicated backend management tasks, thus resolving the contradiction between improved resource utilization and increased management complexity
Solution Approach 2:
The resource manager is designed as a universal system that handles multiple functions including resource reservation, allocation, monitoring, and pricing for diverse computing resources (CPU, memory, storage, networking) across multiple data centers. This multi-functional approach consolidates various management tasks into a single system, reducing overall management complexity while maintaining high resource utilization efficiency
2Productivity
If resource pricing fluctuates dynamically in response to demand and supply, then resource allocation efficiency is improved, but client satisfaction may suffer due to unpredictable pricing
Solution Approach 1:
The patent implements resource reservation mechanisms that allow customers to pre-book computing resources at predetermined prices before actual usage. This preliminary action locks in pricing and resource allocation in advance, providing price predictability and customer satisfaction while still allowing dynamic pricing for non-reserved resources, thus resolving the contradiction between allocation efficiency and client satisfaction
Solution Approach 2:
The system implements dynamic pricing for non-reserved resources that fluctuates in response to real-time demand and supply conditions. The resource manager continuously adjusts pricing for on-demand resources based on current utilization levels, while reserved resources maintain fixed pricing. This dynamic approach optimizes allocation efficiency for flexible resources while providing stability for committed resources, balancing both objectives
3Reliability
If multiple data centers are used to distribute computing resources, then service availability is improved, but resource allocation complexity increases
Solution Approach 1:
The resource manager is designed as a universal control system that manages computing resources across multiple geographically distributed data centers through a single unified interface. It handles resource reservation, allocation, and monitoring across all data centers centrally, providing service availability through multi-location deployment while avoiding the complexity of distributed management by consolidating control functions
Solution Approach 2:
The patent segments the resource management system into modular components including resource reservation modules, allocation modules, monitoring modules, and pricing modules that can operate independently across different data centers. Each data center can be managed as a semi-independent unit while still being part of the overall distributed system, reducing allocation complexity through modular architecture while maintaining service availability across locations
Data Source
AI summary
Methods and apparatus for flexible-location reservations and pricing for network-accessible resources are disclosed. A system includes a plurality of resources of a provider network distributed across multiple locations, and a resource manager. The resource manager implements a programmatic interface to allow a client to specify a flexible location option for a resource reservation request, indicating that the resource manager is to select one or more locations at which to reserve resource capacity. When a reservation request with the flexible location option specified is received, the resource manager selects a particular location based at least in part on heuristics using resource utilization data. In response to a resource activation request for the reservation, the resource manager activates a resource at a launch location selected from the multiple locations.