Dynamic Data Placement Using Tags in Edge Nodes

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Solution Overview

Problem

Existing data placement techniques in edge environments are inflexible and often prioritize a single objective, such as minimizing network latency or storage capacity, which can lead to inefficient data placement and poor performance, including overflow of local buffers, dropped connections, and increased environmental footprint due to costly upgrades.

Innovation Solution

Implementing a dynamic data placement system that uses tags associated with data objects to identify destination components based on multiple criteria prioritized within a placement policy, allowing for adaptable and efficient data routing without the need for extensive resource analysis or storage at edge nodes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If existing data placement techniques prioritize a single objective such as minimizing network latency or storage capacity, then that specific objective is improved, but data placement efficiency deteriorates and causes overflow of local buffers, dropped connections, and poor overall performance

Engineering Contradiction:

Improvenetwork latencyVSAvoiddata placement efficiency

Core Design Contradiction:

SpeedVSProductivity

Solution Approach 1:

The system dynamically adjusts data placement decisions based on multiple changing criteria including network conditions, storage availability, and data characteristics. The placement policy evaluates multiple objectives simultaneously rather than fixing on a single static criterion, allowing the system to adapt to varying conditions and avoid the pitfalls of single-objective optimization.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the parameters used for data placement from single-objective to multi-objective evaluation. By considering multiple criteria (latency, storage capacity, buffer status, connection stability) simultaneously, the system transforms the decision-making process to balance competing requirements and achieve overall placement efficiency rather than optimizing one parameter at the expense of others.

Inventive Principle:

Principle #35Parameter changes

2Quantity of substance

If edge nodes store more data locally to reduce transmission, then storage capacity increases, but storage space at edge nodes becomes limited and causes overflow of local buffers

Engineering Contradiction:

Improvedata storage capacityVSAvoidbuffer overflow prevention

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The system performs preliminary evaluation of edge node buffer status and storage capacity before making data placement decisions. By checking buffer availability and storage space in advance, the system can determine whether local storage is appropriate or if data should be transmitted elsewhere, preventing buffer overflow before it occurs.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors buffer status, storage capacity, and data placement outcomes at edge nodes. This feedback mechanism allows the system to adjust placement decisions in real-time, reducing data to nodes with available capacity and preventing overflow by responding to current system state rather than using static storage allocation.

Inventive Principle:

Principle #23Feedback

3Measurement precision

If edge nodes perform extensive resource analysis for data placement, then placement accuracy improves, but resource consumption and processing time increase

Engineering Contradiction:

Improveplacement accuracyVSAvoidresource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system performs a focused evaluation of the most critical placement criteria rather than exhaustive analysis of all possible factors. By identifying and prioritizing key decision factors (such as buffer status, storage capacity, and network conditions), the system achieves sufficient placement accuracy without the excessive resource consumption of complete resource analysis.

Inventive Principle:

Principle #16Partial or excessive action

4Productivity

If edge nodes handle large data volumes from numerous client devices, then data processing capacity increases, but storage space becomes limited and performance deteriorates

Engineering Contradiction:

Improvedata processing capacityVSAvoidstorage space

Core Design Contradiction:

ProductivityVSArea of stationary object

Solution Approach 1:

The system segments the data placement decision-making process into evaluation and execution phases, and segments storage responsibilities across multiple destination nodes. By dividing incoming data streams and distributing them based on real-time capacity assessment, the system can handle large data volumes without any single edge node becoming a storage bottleneck.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11611619B2Policy-based data placement in an edge environment

Publication Date: 2023.03.21 RED HAT LLC

AI summary

Data can be placed by an edge node in a computing environment using multiple criteria in a placement policy. For example, a processing device of an edge node can receive a write request for storing a data object. The processing device can select first and second criteria from a placement policy based on a tag for the data object. The processing device can determine a set of remote components that fulfill the first criterion. The processing device can then identify, from the set, a destination component that fulfills the second criterion. The processing device can transmit the data object to the destination component.