Multi-Cloud Allocation Broker Resolving Resource Conflicts
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Solution Overview
Problem
Current cloud management systems lack a uniform and extensible approach to allocate or de-allocate resources across multiple different cloud systems, leading to resource constraints and conflicts due to varying configurations and implementations.
Innovation Solution
A system and method for resource allocation in a multi-cloud environment, where an allocation broker receives client requests to create allocations across multiple clouds, utilizing reservation brokers and handlers to identify and manage sufficient resource quotas, ensuring consistent and uniform resource allocation and de-allocation across diverse cloud systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different cloud systems use their own resource allocation approaches, then each cloud system can be optimized for its specific implementation, but there is no uniform way to allocate or de-allocate resources across multiple cloud systems
Solution Approach 1:
The patent introduces a resource allocation service as an intermediary layer between cloud service consumers and multiple cloud systems. This service receives allocation requests, determines appropriate cloud systems and parameters, and manages the allocation process uniformly. The intermediary abstracts the complexity of individual cloud system implementations while maintaining optimized access to each, resolving the contradiction between adaptability and complexity.
2Reliability
If cloud resources are reserved to prevent constraints and conflicts, then resource availability is improved, but resources need to be allocated before use and de-allocated when not needed
Solution Approach 1:
The patent implements preliminary resource reservation where cloud resources are reserved in advance for cloud service consumers before actual allocation occurs. This preliminary action ensures resource availability and prevents constraints when resources are needed. The system maintains reservation information and can quickly allocate from pre-reserved pools, reducing the time loss associated with finding and allocating resources at the moment of need.
3Productivity
If cloud resources are shared across multiple consumers, then resource utilization efficiency is improved, but runtime conflicts occur when resources are concurrently accessed
Solution Approach 1:
The patent implements a feedback mechanism where the resource allocation service monitors resource usage, availability, and conflict conditions across cloud systems. When runtime conflicts are detected or predicted, the service adjusts allocation decisions, redirects requests to alternative resources, or coordinates access timing. This feedback loop maintains high resource utilization by enabling sharing while preventing or resolving conflicts that would compromise access stability.
Data Source
AI summary
An example method for allocating resources in a multi-cloud environment may include receiving, by an allocation broker executing in the multi-cloud environment, a client request to create an allocation of cloud resource in a plurality of clouds. The method may include receiving, by the allocation broker from a reservation broker, a reservation candidate based on a reservation type. The reservation candidate is associated with a cloud, and the cloud corresponds to a cloud broker. The method may further include invoking, by the allocation broker, a location handler corresponding to the reservation type to identify a reservation in the cloud having sufficient resource quota to support the allocation of cloud resource, and invoking, by the allocation broker, an allocation handler corresponding to the reservation type to create the allocation of cloud resource in the reservation.