Videoconferencing Bit Rate Calculation Using Historical Data
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Solution Overview
Problem
Videoconferencing devices face quality issues due to bandwidth fluctuations, where the initial transmit bit rate may exceed or be lower than the channel's capacity, leading to packet loss or underutilization of bandwidth, despite dynamic bandwidth adaptation techniques.
Innovation Solution
A method and apparatus for videoconferencing devices that maintain a database of bit rate information to calculate an initial video bit rate based on previous sessions with target endpoints and endpoints in the same zone, using weighted averages to determine an optimal initial bit rate for transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the initial transmit bit rate is set high to maximize video quality, then video quality is improved, but packet loss increases when bandwidth fluctuates
Solution Approach 1:
The system performs preliminary actions by maintaining a database of bit rate information from previous videoconferencing sessions with the target endpoint and endpoints in common zones. Before initiating the videoconference call, the system identifies relevant records and calculates an optimized initial video bit rate based on historical data, thereby preparing the optimal transmission parameters in advance to prevent packet loss while maintaining video quality.
Solution Approach 2:
The system uses feedback from historical performance data stored in the database to adjust the initial bit rate selection. By analyzing bit rate information from previous sessions and calculating weighted averages, the system learns from past transmission outcomes and uses this feedback to make informed decisions about the initial bit rate, balancing video quality and packet loss prevention.
2Reliability
If the initial transmit bit rate is set low to prevent packet loss, then packet loss is reduced, but channel bandwidth utilization decreases
Solution Approach 1:
The system performs preliminary actions by calculating the initial video bit rate before the videoconference call starts, using historical bit rate information from the database. This pre-calculation ensures that the initial bit rate is optimized to maximize bandwidth utilization without causing packet loss, rather than using a conservative low bit rate that would underutilize the channel.
Solution Approach 2:
The system dynamically changes the bit rate parameter based on historical data analysis. By calculating weighted averages of previous bit rates and adjusting the initial bit rate parameter accordingly, the system adapts to the specific channel characteristics and endpoint capabilities, achieving optimal bandwidth utilization while preventing packet loss.
3Productivity
If dynamic bandwidth adaptation is used to adjust bit rate during the call, then bandwidth utilization is improved, but initial packet loss occurs before adaptation can take effect
Solution Approach 1:
The system performs the critical action of calculating and setting the initial video bit rate before the videoconference call begins. By using historical bit rate information from the database and calculating weighted averages, the system establishes the optimal initial bit rate in advance, preventing initial packet loss that would otherwise occur before dynamic bandwidth adaptation could respond to bandwidth conditions.
Solution Approach 2:
The system takes preliminary anti-action by pre-calculating the optimal initial bit rate to counteract potential packet loss before it occurs. This proactive approach addresses the bandwidth adaptation delay issue by establishing the correct bit rate from the start, preventing the initial packet loss problem that dynamic adaptation alone cannot solve.
4Device complexity
If a fixed bit rate is used for all videoconferencing sessions, then device complexity is reduced, but adaptability to different bandwidth conditions deteriorates
Solution Approach 1:
The system implements self-service by automatically maintaining a database of bit rate information and performing calculations to determine the optimal initial video bit rate without requiring manual configuration or complex real-time analysis. The system serves itself by learning from historical data and making intelligent bit rate selections, achieving adaptability through automated data-driven decision-making rather than complex manual control mechanisms.
Data Source
AI summary
A method performed by a videoconferencing device, the method comprising: maintaining a database (129) comprising multiple records, each record including bit rate information and relating to a particular endpoint identifier; initiating a videoconference call with a target endpoint (101, 103); identifying (S2) one or more records in the database (129) that relate to the endpoint identifier of the target endpoint (101, 103); identifying (S5) one or more records in the database (129) that relate to the endpoint identifier of one or more endpoints located in a common zone with the target endpoint (101, 103); using bit rate information from the identified records to calculate (S4, S7, S8) an initial video bit rate for the videoconference call; and initially transmitting video to the target endpoint (101, 103) at the calculated initial video bit rate. Apparatus configured to implement the foregoing method.