Deferrable Data Flow for Cloud Resource Management
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Solution Overview
Problem
Cloud computing devices face overburden and slower service due to increased demand, as real-time operations and communication between distributed resources become inefficient, leading to inconsistent performance.
Innovation Solution
Implementing a method to manage computational resources by deferring non-essential operations associated with inactive pages, allowing only operations affecting active pages to be executed in real-time, and scheduling others based on resource availability and latency, using a dependency graph to optimize data flows and reduce processing load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If real-time operations are implemented for all cloud services, then service responsiveness is improved, but resource burden increases and service consistency deteriorates
Solution Approach 1:
The system performs preliminary analysis to identify which operations are view-dependent and can be deferred. By pre-classifying operations into immediate and deferrable categories based on their relationship to active displays, the system prepares execution schedules in advance, allowing non-critical operations to be delayed without impacting user perception of service responsiveness.
Solution Approach 2:
The system dynamically adjusts operation execution timing based on current display state. Operations are re-evaluated against the active display context, and their execution schedules are flexibly modified. This dynamic approach allows the system to prioritize operations affecting currently visible content while deferring those that do not, maintaining responsiveness where it matters most.
2Reliability
If all operations are executed immediately, then processing completeness is improved, but memory consumption and network bandwidth increase
Solution Approach 1:
The system performs preliminary identification of view-dependent operations and schedules them for deferred execution. By analyzing the dependency relationship between operations and active displays in advance, the system can postpone non-essential operations without compromising eventual processing completeness, thereby reducing immediate memory and network resource requirements.
Solution Approach 2:
The system temporarily discards execution of deferrable operations, keeping them in a scheduled state rather than immediately processing them. These operations are recovered and executed later when resources are available or when their associated displays become active, ensuring processing completeness is maintained while reducing peak resource consumption.
3Reliability
If distributed resources communicate in real-time, then service coordination is improved, but communication overhead increases
Solution Approach 1:
The system performs preliminary analysis to identify operations that can be deferred based on display activity. By pre-determining which operations are view-dependent, the system avoids immediate real-time communication for non-critical operations, reducing communication overhead while maintaining service coordination for operations that truly require timely execution.
Solution Approach 2:
The system dynamically adjusts communication timing based on which displays are currently active. Communication between distributed resources is scheduled flexibly, prioritizing coordination for operations affecting visible content while deferring coordination for background or inactive operations, thereby reducing overall communication overhead while maintaining necessary service coordination.
Data Source
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AI summary
Examples of the disclosure enable one or more operations to be executed or implemented while managing computational resources. In some examples, an instruction to implement a first operation is received. The first operation is associated with a first node of a plurality of nodes. The plurality of nodes are arranged in a plurality of regions. A second node of the plurality of nodes that is related to the first node is identified. On condition that the second node is arranged in an active region of the plurality of regions, a second operation associated with the second node is implemented within a period of time. On condition that the second node is not arranged in the active region, the second operation is not implemented within the period of time. Aspects of the disclosure enable a computing device to defer the implementation of an operation to facilitate managing computational resources.