Virtual Machine Task Scheduling by Expiration Time
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Solution Overview
Problem
Virtual machines with expiration times face challenges in efficiently managing tasks within their limited resource allocation periods, leading to potential task abandonment or resource reallocation issues when estimated task completion time exceeds the remaining expiration time.
Innovation Solution
A method where if a task's estimated time exceeds a virtual machine's remaining expiration time, the system either allows automatic extension, user intervention for extension, or reallocates the task to another virtual machine with sufficient resources and a shorter estimated completion time, ensuring timely task completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a task is assigned to a virtual machine with limited remaining time, then the virtual machine can be utilized efficiently, but the task may not be completed before expiration
Solution Approach 1:
The system performs preliminary estimation of task completion time before assigning the task to a virtual machine. By comparing the estimated completion time with the remaining expiration time of the virtual machine, the system proactively prevents task expiration by selecting appropriate virtual machines in advance, thus ensuring both utilization efficiency and completion reliability
Solution Approach 2:
The system continuously monitors the remaining expiration time of virtual machines and compares it with the estimated task completion time. This feedback mechanism allows dynamic task assignment decisions, where tasks are redirected to different virtual machines based on real-time time availability, ensuring tasks complete before expiration while maximizing virtual machine utilization
2Reliability
If a task is reassigned to another virtual machine, then task completion is ensured, but system complexity increases
Solution Approach 1:
The system implements automated task management where the task assignment and reassignment process occurs without manual intervention. The system autonomously estimates completion times, compares them with virtual machine expiration times, and performs reassignment when necessary, reducing management complexity while ensuring task completion
Solution Approach 2:
The system uses quantitative parameters (estimated completion time, remaining expiration time) to drive task assignment decisions. By establishing clear numerical criteria for task reassignment, the system simplifies the management complexity compared to qualitative or manual decision-making processes
Data Source
AI summary
In an embodiment, if an estimated time to perform a task by a first virtual machine is less than or equal to an expiration time of the first virtual machine minus the current time, the task is performed by the first virtual machine. If the estimated time to perform the task by the first virtual machine is greater than the expiration time of the first virtual machine minus the current time, a selected virtual machine is selected from among a plurality of virtual machines with a smallest estimated time to perform the task and a request to perform the task is sent to the selected virtual machine.