Safety-Aware Task Orchestration Across Edge and Cloud Resources
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Solution Overview
Problem
Distributing tasks statically across computing environments leads to resource underutilization and inefficient use of resources, with critical tasks waiting due to unavailable resources, while expensive resources are used for less critical tasks.
Innovation Solution
Implementing a safety-aware orchestrator that dynamically distributes safety-critical services across the compute continuum, leveraging diverse resources for redundancy and diversity, allowing for run-time provisioning and distribution of tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tasks are distributed statically across computing environments, then resource allocation is simplified and predictable, but resource utilization is low and critical tasks may not be performed timely
Solution Approach 1:
The patent implements dynamic task distribution by continuously monitoring resource availability and task priorities, then reallocating tasks between cloud and edge computing environments at runtime. This allows the system to adapt to changing conditions, ensuring critical tasks are executed on available resources while maximizing overall resource utilization across the distributed computing infrastructure.
2Reliability
If expensive resources are allocated to all tasks, then task execution reliability is improved, but cost increases and resources are wasted on non-critical tasks
Solution Approach 1:
The patent applies different resource allocation strategies to different task types based on their criticality. Safety-critical tasks receive guaranteed allocation of reliable resources (such as edge computing resources with dedicated hardware), while non-critical tasks utilize available cloud resources. This localized quality approach ensures reliability where needed while optimizing overall resource consumption.
3Reliability
If dedicated hardware is reserved for safety-critical services, then safety assurance is maintained, but system flexibility is reduced and hardware upgrades are required for service additions
Solution Approach 1:
The patent creates a multi-functional computing architecture where edge computing nodes serve dual purposes: they provide dedicated hardware resources for safety-critical tasks requiring high reliability, while simultaneously serving as part of the general-purpose cloud computing infrastructure for non-critical tasks. This universal approach allows the same hardware to fulfill multiple roles, enabling service additions without dedicated hardware upgrades.
4Device complexity
If critical tasks wait for resource availability, then resource allocation is simplified, but task completion time increases and system responsiveness decreases
Solution Approach 1:
The patent implements a feedback-driven resource management system that continuously monitors resource availability, task priorities, and system state. Based on this real-time feedback, the orchestrator dynamically adjusts task allocation decisions, proactively assigning critical tasks to available resources before they are needed, thereby reducing waiting time while maintaining manageable complexity through automated decision-making.
Data Source
AI summary
Disclosed herein are systems and methods for dynamically distributing a safety, awareness task. The systems and methods may include receiving hardware resources data associated with a plurality of remote computing systems. A plurality of safety assurance profiles may be received. Each of the plurality of safety assurance profiles may be associated with a respective service. A safety assurance task may be dynamically assigned to one of the plurality of remote computing systems based on the hardware resources data and one of the plurality of safety assurance profiles.