PATENT CLAIM ANALYSIS

Application Number: 15903624
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["709", "226000"]

Abstract:
Embodiments of the present invention provide an approach for policy-driven (e.g., price-sensitive) scaling of computing resources in a networked computing environment (e.g., a cloud computing environment). In a typical embodiment, a workload request for a customer will be received and a set of computing resources available to process the workload request will be identified. It will then be determined whether the set of computing resources are sufficient to process the workload request. If the set of computing resources are under-allocated (or are over-allocated), a resource scaling policy may be accessed. The set of computing resources may then be scaled based on the resource scaling policy, so that the workload request can be efficiently processed while maintaining compliance with the resource scaling policy.

Claim (Index 19):
The computer program product of  claim 18 , the computer readable storage media further comprising instructions to at least one of:\n provision additional computing resources to the set of computing resources based on the need without exceeding the pricing constraint, or de-provision computing resources from the set of computing resources to avoid exceeding the pricing constraint.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 2.09091
- Patent Class: 709.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13343293', '14590276', '13195326', '13220879', '14950173']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2971207995550565
- 35 USC 102 Novelty (BERT): 0.5388150668339814
- Combined Prediction Score: 0.321290226282949
- Mean Citation Score: 306.532414
- Max Citation Score: 412.7507
- Similarity Product: 286.026279022944

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

Dataset: test