Patent №
US 11,455,188
Granted
2022-09-27
Filed 2020
Owner
UNIVERSITY OF LOUISIANA AT LAFAYETTE
Lab
—
AI components
1
hardware
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
16860286
Disclosed is a method for task pruning that can be utilized in existing resource allocation systems to improve the systems' robustness without requiring changing to existing mapping heuristics. The pruning mechanism leverages a probability model, which calculates the probability of a task competing before its deadline in the presence of task dropping, and only schedules tasks that are likely to succeed. Pruning tasks whose chance of success is low improves the chance of success for other tasks. Tasks that are unlikely to succeed are either deferred from current scheduling event or are preemptively dropped from the system. The pruning method can benefit service providers by allowing them to utilize their resources more efficiently and use them only for tasks that can meet their deadlines. The pruning method further helps end users by making the system more robust in allowing more tasks to complete on time.
AI classification
Ownership
UNIVERSITY OF LOUISIANA AT LAFAYETTE
assignment · 532510698
Assignors
JAMES GENTRY, MOHSEN AMINI SALEHI, CHAVIT DENNINNART
On an employer assignment, the assignors are typically the inventors.