Fog Computing Platform Priority-Based Compute Offload Allocation
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Solution Overview
Problem
Mobile devices and IoT devices face challenges with limited computational resources and power supplies, necessitating the offloading of computational tasks to cloud platforms or edge devices, which requires efficient allocation of compute resources.
Innovation Solution
A fog computing platform allocates compute resources based on user standing, determined by a score computed from various factors such as social media influence, loyalty programs, and device characteristics, to prioritize resource access for trusted users over unknown users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If computational tasks are offloaded to cloud platforms or edge devices, then computational resources are improved, but resource allocation efficiency deteriorates without priority-based management
Solution Approach 1:
The system changes the parameter of resource allocation by introducing priority levels associated with different users or devices. The fog computing platform allocates computational resources differently based on these priority parameters, ensuring that high-priority requests receive sufficient resources while maintaining overall system efficiency.
Solution Approach 2:
The patent applies local quality by providing differentiated resource allocation to different users or devices based on their specific priority levels. Instead of uniform resource distribution, the system tailors resource allocation to local needs and priorities of individual requests.
2Loss of time
If computational tasks are offloaded to edge devices, then latency is reduced, but resource contention increases without priority management
Solution Approach 1:
The system introduces priority level parameters to manage resource contention at the edge. By associating different priority levels with different users or devices, the fog computing platform ensures that time-sensitive, high-priority tasks receive immediate resource allocation, reducing latency while maintaining reliable resource availability for all users.
3Productivity
If computational resources are shared among multiple devices, then resource utilization is improved, but service quality deteriorates without differentiated allocation
Solution Approach 1:
The patent implements local quality by providing differentiated service quality to different users based on their priority levels while maintaining high resource utilization. High-priority users receive guaranteed service quality and resource allocation, while lower-priority users share remaining resources, ensuring overall system productivity.
Solution Approach 2:
The system changes the resource allocation parameter from uniform distribution to priority-based distribution. This allows the fog computing platform to maintain high resource utilization by allocating resources to high-priority requests first, while still providing service to lower-priority requests with available capacity.
Data Source
AI summary
Systems, methods, and computer program products to perform an operation comprising receiving, by a fog computing platform, a request from a wireless device to perform a compute task on behalf of the wireless device, determining a first computing resource, of a plurality of computing resources, required to perform the compute task, associating the request with a first level of priority, of a plurality of levels of priority, for accessing the first computing resource, allocating, based at least in part on the first level of priority, a portion of the first computing resource to perform the requested compute task.