Edge Task Scheduling via Travel Plan Coordination
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Solution Overview
Problem
In collaborative computing environments, scheduling computer tasks across a mix of stationary and moving edge computing devices is challenging due to varying resource availability, location, and network connectivity, leading to issues with task offloading and processing efficiency.
Innovation Solution
A method and system that automatically identify and select suitable edge computing devices by correlating computer resource information, location, network information, and travel information with scheduled task times to optimize task offloading and processing, especially for moving edge devices by coordinating with their travel plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If tasks are scheduled on moving edge computing devices, then task processing flexibility and resource utilization are improved, but task completion reliability deteriorates due to unpredictable availability and connectivity changes
Solution Approach 1:
The system performs preliminary actions by detecting travel information and predicting future locations of moving edge devices before task execution. It proactively identifies devices that will be available at specific future times and locations, allowing tasks to be scheduled in advance with confidence in device availability, thus maintaining reliability while enabling flexibility.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring the actual locations and availability of moving edge devices against predicted trajectories. This feedback loop allows the scheduling system to adjust task assignments dynamically, ensuring that tasks are assigned to devices that will actually be available, thereby maintaining high task completion reliability despite device mobility.
2Measurement precision
If task scheduling considers travel information and location data, then device selection accuracy is improved, but system complexity increases due to additional data processing requirements
Solution Approach 1:
The system extracts only the essential travel information and location data needed for task scheduling decisions, rather than processing all available device data. By selectively extracting relevant mobility parameters (current location, speed, direction, predicted trajectory), the system achieves accurate device selection without the overhead of comprehensive data processing, thus reducing system complexity while maintaining precision.
3Productivity
If tasks are offloaded to moving edge devices, then resource utilization is improved, but task processing time variability increases due to device mobility and connectivity changes
Solution Approach 1:
The system performs preliminary identification of suitable moving edge devices based on their predicted trajectories and availability windows before task offloading. By pre-calculating which devices will be available at specific locations and times, the system can assign tasks with predictable completion times, reducing time variability while maximizing resource utilization through mobile device participation.
Data Source
AI summary
A method for automatically selecting a computing device to offload and process a computer task is provided. The method may include automatically identifying an off-loadable computer task to be offloaded from a first computing device to a second computing device. The method may further include determining a scheduled time and an amount of time for processing the identified off-loadable computer task. The method may further include, based on the identified off-loadable computer task, the scheduled time, and the determined amount of time, automatically identifying available computing devices from the plurality of computing devices for processing the identified off-loadable computer task. The method may further include, selecting the computing device from for processing the off-loadable computer task, wherein selecting a moving edge computing device further includes coordinating the scheduled time and the amount of time for processing the identified off-loadable computer task with a determined travel plan.