Policy-Based Resource Exchange Context in Distributed Data Centers
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Solution Overview
Problem
Current distributed computing systems face challenges in effectively sharing and exchanging computational resources among multiple organizations, leading to inefficiencies in resource utilization and management, particularly due to the difficulty in seamlessly migrating virtual machines and balancing resource capacities across data centers.
Innovation Solution
A distributed resource-exchange system that employs efficient search methods and a policy-based context to facilitate the sharing of computational resources by matching resource providers with consumers, utilizing a cloud-exchange engine to manage resource allocation and financial transactions, thereby optimizing resource usage across geographically distributed data centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated resource-exchange systems are implemented to share computational resources among distributed computing facilities, then resource utilization efficiency improves, but system complexity and difficulty of managing resource exchange operations increase
Solution Approach 1:
The patent segments the resource-exchange process into distinct operational stages (initiation, execution, completion, cancellation) and represents each stage as a separate state in a finite-state machine. This segmentation allows complex resource exchange operations to be broken down into manageable, well-defined transitions, reducing the overall system complexity while maintaining efficient resource utilization.
Solution Approach 2:
The patent introduces a resource-exchange context as an intermediary mechanism that mediates between resource providers and consumers. This context acts as a state holder that tracks and manages the progression of resource exchange operations through defined states, simplifying the management complexity by providing a centralized control structure rather than direct peer-to-peer coordination.
2Reliability
If policy-based resource-exchange contexts are used to track resource exchange operations, then operational control and monitoring improve, but information management complexity increases
Solution Approach 1:
The patent uses parameter changes to represent state transitions in the resource-exchange context. Each state is defined by specific parameters (such as exchange status, progression stage), and transitions between states involve changing these parameters according to defined rules. This approach improves operational control through clear parameter-based state management while reducing information management complexity by using standardized parameter sets rather than complex data structures.
Solution Approach 2:
The resource-exchange context serves multiple functions simultaneously: it tracks operation progression, stores state information, manages transitions, and provides monitoring capabilities. By designing a universal context structure that handles all these functions within a single mechanism, the patent reduces information management complexity compared to using separate systems for each function while maintaining reliable operational control.
3Measurement precision
If distributed search methods are employed to locate matching resource providers, then resource matching accuracy improves, but search and coordination time increases
Solution Approach 1:
The patent performs preliminary actions by pre-defining resource requirements and provider attributes before the actual resource exchange occurs. The system establishes search criteria and resource specifications in advance, allowing distributed search methods to quickly match pre-categorized resources rather than performing comprehensive searches during execution. This reduces search and coordination time while maintaining high matching accuracy through pre-established criteria.
Data Source
AI summary
The current document is directed to a resource-exchange system that facilitates resource exchange and sharing among computing facilities. The currently disclosed methods and systems employ efficient, distributed-search methods and subsystems within distributed computer systems that include large numbers of geographically distributed data centers to locate resource-provider computing facilities that match the resource needs of resource-consumer computing-facilities based on attribute values associated with the needed resources, the resource providers, and the resource consumers. The resource-exchange system organizes and tracks operations related to a resource exchange using a resource-exchange context. In one implementation, each resource-exchange context represents the stages of, and information related to, placement of one or more computational-resources-consuming entities on behalf of a resource consumer within a resource-provider computing facility and execution of the one or more computational-resources-consuming entities within the resource-provider computing facility.