Task Scheduling via Capacity-Matched LIFO Allocation
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Solution Overview
Problem
Conventional scheduling techniques for multiplexing tasks in data processing and communication systems are inefficient, leading to suboptimal utilization of limited resources, as they typically allocate tasks based on a first-in, first-out basis, resulting in insufficient remaining capacity for larger tasks and reduced effective channel capacity.
Innovation Solution
A method and system that allocate tasks to processing channels based on maximizing total frame utilization by selecting channels where tasks can be performed and utilize as much remaining capacity as possible, prioritizing larger tasks to increase channel efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional FIFO scheduling techniques are used to allocate tasks to processing channels, then tasks are allocated in first-in-first-out order, but total frame utilization is suboptimal and remaining capacity is insufficient for larger tasks
Solution Approach 1:
The patent inverts the conventional FIFO approach by implementing a LIFO (Last-In-First-Out) scheduling mechanism. Instead of allocating tasks in the order they arrive, the system allocates the most recently arrived task first, allowing larger tasks that arrive later to be prioritized and properly fitted into available channel capacity, thereby improving total frame utilization
Solution Approach 2:
The patent changes the scheduling parameter from time-based FIFO ordering to capacity-based LIFO ordering. By evaluating task size requirements against remaining channel capacity and reversing the allocation priority, the system optimizes frame utilization without requiring additional hardware resources
2Productivity
If additional processing resources are added to increase transmission capacity, then more tasks can be handled, but hardware costs and spaceflight costs are high
Solution Approach 1:
The patent makes existing processing channels multi-functional by dynamically reallocating their capacity based on task requirements. The same channel can serve different task sizes at different times, maximizing the utility of existing hardware resources without requiring additional satellites or processing equipment
Solution Approach 2:
The patent introduces dynamic task allocation where channel assignments are not fixed but adapt based on the size and requirements of incoming tasks. This dynamic reallocation allows the system to handle variable workloads efficiently using the same hardware resources, eliminating the need for additional capacity
3Productivity
If processing channels are allocated to maximize remaining capacity for future tasks, then smaller tasks can be accommodated, but larger tasks cannot be performed
Solution Approach 1:
The patent performs preliminary evaluation of task size requirements before allocation. By assessing the size of incoming tasks in advance and reversing the allocation priority, the system ensures that larger tasks are accommodated first when capacity is available, preventing fragmentation that would prevent future large task execution
Data Source
AI summary
Methods and systems for implementing methods for allocating available service capacity to a plurality of tasks in a data processing system having a plurality of processing channels is provided, where each processing channel is utilized in accordance with a time division multiplex processing scheme. A method can include receiving in the data processing system the plurality of tasks to be allocated to the available service capacity and determining a task from among an unassigned set of the plurality of tasks having a requirement for available service capacity which is greatest. The method can also include identifying at least one of the plurality of processing channels that has an available service capacity greater than or equal to the requirement and selectively assigning the task to the processing channel having a remaining service capacity which least exceeds the requirement.