PATENT CLAIM ANALYSIS

Application Number: 15926260
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-07
Patent Classification: ["718", "100000"]

Abstract:
Embodiments presented herein disclose adaptive techniques for scheduling self-maintenance processes. A load predictor estimates, based on a current state of a distributed storage system, an amount of resources of the system required to perform each of a plurality of self-maintenance processes. A maintenance process scheduler estimates, based on one or more inputs, an amount of resources of the distributed system available to perform one or more of the self-maintenance processes during at least a first time period. The maintenance process scheduler determines a schedule for the one or more of the self-maintenance processes to perform during the first time period, based on the estimated amount of resources required and available.

Claim (Index 9):
The computer-readable storage medium of  claim 8 , wherein the one or more inputs includes at least one of a plurality of current activities of the primary storage server and the plurality of secondary storage servers, the current state of the primary storage server and the state of the plurality of secondary storage servers, a plurality of external events, and the estimated amount of computing resources of the primary storage server and the plurality of secondary storage servers required to perform each of the self-maintenance processes.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 2.24528
- Patent Class: 718.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14852249', '10934076', '11985909', '13093645', '14795797']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4008189832037927
- 35 USC 102 Novelty (BERT): 0.5470220429023303
- Combined Prediction Score: 0.4154392891736465
- Mean Citation Score: 173.127426
- Max Citation Score: 328.01706
- Similarity Product: 305.68641842351667

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

Dataset: test