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 29):
The system of  claim 16 , wherein the storage is configured as Redundant Array of Independent Disk (RAID) ranks, wherein each of the RAID ranks is comprised of storage devices, and wherein there are a set of queues for each of the RAID ranks queueing requests for the RAID rank, wherein the queues in each set of queues include requests of different priorities, wherein the input I/O statistics include, for each of the RAID ranks, at least one of.\n a number of active commands on the RAID rank for each of the queues in the set of queues for the RAID rank; an average response time for writes to the RAID rank in each of the queues queueing tracks for the RAID rank; an average response time for reads to the RAID rank in each of the queues queueing tracks for the RAID rank; rank type based on a speed of type of storage device storing tracks for the RAID rank; RAID level; and indication of whether raid RANK is undergoing preemptive reconstruction.

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): 0.6263739574194126
- 35 USC 102 Novelty (BERT): 0.5018831689666593
- Combined Prediction Score: 0.6139248785741372
- Mean Citation Score: 193.22275
- Max Citation Score: 201.68234
- Similarity Product: 123.49646373107792

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