PATENT CLAIM ANALYSIS

Application Number: 15871930
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["370", "235000"]

Abstract:
Systems and methods for optimizing system performance of capacity and spectrum constrained, multiple-access communication systems by selectively discarding packets are provided. The systems and methods provided herein can drive changes in the communication system using control responses. One such control responses includes the optimal discard (also referred to herein as “intelligent discard”) of network packets under capacity constrained conditions. The systems and methods prioritize packets and make discard decisions based upon the prioritization. Some embodiments provide an interactive response by selectively discarding packets to enhance perceived and actual system throughput, other embodiments provide a reactive response by selectively discarding data packets based on their relative impact to service quality to mitigate oversubscription, others provide a proactive response by discarding packets based on predicted oversubscription, and others provide a combination thereof.

Claim (Index 17):
The method of  claim 12 , wherein the selected video frame discard level for each of the one or more determined video services is applied to a group of pictures (GOP) based at least in part on a priority value for each frame in the GOP.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 86.0
- Lexical Diversity: 1.7439
- Patent Class: 370.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15225306', '13953422', '13182703', '13243507', '14076512']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.639777379380576
- 35 USC 102 Novelty (BERT): 0.5421397049203115
- Combined Prediction Score: 0.6300136119345495
- Mean Citation Score: 375.926616
- Max Citation Score: 418.86517
- Similarity Product: 270.49578437408445

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