PATENT CLAIM ANALYSIS

Application Number: 15984201
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-11
Patent Classification: ["710", "220000"]

Abstract:
Provided are a computer program product, system, and method for using at least one machine learning module to select a priority queue from which to process an Input/Output (I/O) request. Input I/O statistics are provided on processing of I/O requests at the queues to at least one machine learning module. Output is received from the at least one machine learning module for each of the queues. The output for each queue indicates a likelihood that selection of an I/O request from the queue will maintain desired response time ratios between the queues. The received output for each of the queues is used to select a queue of the queues. An I/O request from the selected queue is processed.

Claim (Index 28):
The system of  claim 18 , wherein the input I/O statistics include at least one I/O statistic for the queues that is member of a set of I/O statistics comprising:\n a queue depth for each of the queues indicating a number of requests queued in each of the queues; a number of active commands in each of the queues; an average response time for reads in each of the queues; an average response time for writes in each of the queues; an average number of tracks per request for each of the queues; a time since a request was last accessed from each of the queues; a last queue of the queues that was processed; indication of whether a next request for each of the queues comprises a read or a write; a number of tracks on a next request for each of the queues; and age of a longest I/O request in each of the queues.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 2.06452
- Patent Class: 710.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['12046740', '15628776', '14292123', '11739460', '12240190']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6256178245074921
- 35 USC 102 Novelty (BERT): 0.5051090688820438
- Combined Prediction Score: 0.6135669489449473
- Mean Citation Score: 193.22275
- Max Citation Score: 201.68234
- Similarity Product: 118.57673781383636

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test