What is used together with statistical multiplexing to prevent bit-overflow errors?

Statistical multiplexing is a technique used in data transmission that allows multiple data streams to share the same bandwidth efficiently. However, one of the challenges it faces is the potential for bit-overflow errors, which occur when the data being transmitted exceeds the capacity of the channel due to bursts of activity from one or more sources.

Rate shaping algorithms play a crucial role in mitigating these overflow errors. They work by controlling the data rate of the various streams being multiplexed. By smoothing out peaks in data transmission and ensuring that the data being sent respects the available bandwidth capacity, these algorithms help maintain a consistent and manageable flow of data. This helps to avoid scenarios where too much data is sent at once, which could lead to congestion and overflow.

Other techniques, while valuable in their own rights, do not specifically address the issue of overflow in the context of statistical multiplexing as effectively as rate shaping algorithms do. For example, a single buffer for all channels could lead to complications in managing data flow, and while audio compression and video synchronization techniques are important for their respective purposes, they do not inherently prevent bit-overflow errors in the same way that rate shaping does.