Edge Utility System with Configurable Trust Levels for Dynamic Resource Aggregation
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Solution Overview
Problem
Information processing systems face challenges in efficiently managing resources to meet varying workload demands across multiple edge computing sites, particularly in ensuring adequate resource availability and accessibility for users.
Innovation Solution
The implementation of a user-configurable edge utility system that dynamically aggregates edge resources across multiple edge computing sites, allowing users to specify trust levels for resource providers and select resources based on those levels, facilitating efficient workload execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If edge resources from multiple providers are aggregated to meet varying workload demands, then resource availability and flexibility improve, but trust management complexity increases
Solution Approach 1:
The system changes the parameter of trust from a binary concept to a multi-level spectrum, allowing users to specify trust levels (e.g., high, medium, low) for different resource providers. This enables flexible resource aggregation across multiple providers while managing trust complexity through configurable parameters rather than complex verification protocols.
2Reliability
If users can select resources based on trust levels, then reliability improves, but system complexity increases
Solution Approach 1:
The system performs preliminary trust assessment and resource classification before workload execution. Resource providers are pre-evaluated and assigned trust levels, and users pre-configure their trust preferences. This preliminary action simplifies the actual resource selection process during workload execution, maintaining reliability without adding operational complexity.
3Productivity
If dynamic aggregation of edge resources is implemented, then productivity improves, but coordination overhead increases
Solution Approach 1:
The system implements dynamic resource aggregation where the resource pool adapts in real-time based on workload demands and provider availability. The aggregation logic dynamically selects and combines resources from multiple edge providers, enabling efficient workload servicing while minimizing coordination overhead through automated, demand-driven resource orchestration.
Data Source
AI summary
A method includes receiving from a first user in an edge utility system information specifying a trust level for one or more providers of edge resources, and aggregating edge resources of a plurality of edge computing sites of the edge utility system, the aggregated edge resources including at least edge resources of the one or more providers. The method further includes selecting particular ones of the aggregated edge resources based at least in part on the specified trust level, and utilizing the selected particular ones of the aggregated edge resources to execute at least a portion of a workload of the first user. The method may include tracking trust factors for each of the one or more providers over time, with the selection of particular ones of the aggregated edge resources being based at least in part on the one or more tracked trust factors and the specified trust level.