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 30):
The system of  claim 29 , wherein a plurality of device adaptors manage access to the RAID ranks, wherein each of the device adaptors includes a set of queues for each of the RAID ranks to which the device adaptor connects, wherein each of the device adaptors includes at least one machine learning module to select a queue from a set of the queues for the RAIDS ranks, wherein the input I/O statistics include:\n indication of whether each of the device adaptors is operating standalone or part of pair of device adaptors managing access to RAID ranks.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 2.06452
- Patent Class: 710.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['12046740', '15628776', '14292123', '11739460', '12240190']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6566146889357425
- 35 USC 102 Novelty (BERT): 0.4915254521152151
- Combined Prediction Score: 0.6401057652536897
- Mean Citation Score: 193.22275
- Max Citation Score: 201.68234
- Similarity Product: 142.79738467534068

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