Node Property Matching for Edge Workload Distribution
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Solution Overview
Problem
Edge devices in distributed computing environments face challenges in efficiently executing complex and computationally intensive workloads due to resource constraints and suboptimal workload assignment, leading to overloading and inefficient execution.
Innovation Solution
A system that distributes workloads based on intrinsic and extrinsic node properties, where intrinsic properties are shared and independent of the workload, and extrinsic properties are specific to the workload, ensuring optimal node selection and resource utilization by determining and providing necessary properties to execute the workload efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If workloads are assigned to edge devices without considering node properties, then device complexity and resource provisioning are reduced, but workload execution efficiency deteriorates and devices become overloaded
Solution Approach 1:
The system changes the parameters of workload assignment by introducing a dual-property matching mechanism. Intrinsic properties (device capabilities) and extrinsic properties (workload requirements) are used as parameters to dynamically match workloads with suitable edge devices, transforming the static resource provisioning into a dynamic parameter-based selection process that optimizes both device complexity and execution efficiency
Solution Approach 2:
The system performs preliminary action by pre-defining and cataloging intrinsic properties of edge devices and extrinsic properties of workloads before assignment. This preliminary classification and matching framework is established in advance, enabling efficient workload distribution without requiring complex real-time resource provisioning when workloads arrive
2Ease of operation
If workloads are distributed without node property matching, then ease of operation is improved, but reliability deteriorates due to overloading and single points of failure
Solution Approach 1:
The system implements self-service by enabling edge devices to self-identify their intrinsic properties and workloads to self-describe their extrinsic requirements. The matching system automatically pairs compatible devices and workloads based on property compatibility without manual intervention, maintaining ease of operation while improving reliability through property-based selection that prevents overloading
Solution Approach 2:
The system introduces feedback mechanisms where the matching outcomes are continuously evaluated based on workload execution success and device status. This feedback loop allows the system to learn from past assignments and improve future matching decisions, enhancing system reliability while maintaining operational simplicity through automated adjustments
Data Source
AI summary
Some examples of the present disclosure relate to workload distribution based on node properties. In one particular example, a system can receive a request to execute a workload on at least one node of a set of nodes. The system can determine, based on the request, an intrinsic property that a node of the set of nodes is to include for executing the workload. The intrinsic property can be independent of the workload. The system can determine, based on the request, an extrinsic property that is to be used by the node to execute the workload. The extrinsic property can be dependent on the workload. The system can determine that a first node of the set of nodes includes the intrinsic property. In response to determining that the first node includes the intrinsic property, the system can execute the workload on the first node using the extrinsic property.