Jitter-Adaptive Buffer Switching for Low-Latency Data Streaming
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Solution Overview
Problem
Current computing devices face challenges in managing jitter, which is the transient imbalance between data production and consumption rates, often requiring data dropping or large remote memory buffers, leading to increased power consumption and latency.
Innovation Solution
The implementation of a computing device that dynamically switches between local and remote buffers based on data thresholds, allowing for low-latency and low-power data streaming by using a local buffer for manageable jitter and switching to a remote buffer when necessary, without dropping data or requiring mode changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is buffered in remote memory to manage jitter, then data loss is prevented, but power consumption increases and latency increases
Solution Approach 1:
The memory buffer is segmented into two distinct types: local buffer and remote buffer. The local buffer handles high-speed data transfer with minimal latency for manageable jitter, while the remote buffer provides capacity for larger jitter events. This segmentation allows the system to use appropriate buffer types for different jitter conditions, avoiding the need to always use power-intensive remote buffering.
Solution Approach 2:
The system dynamically switches between local and remote buffer modes based on the current jitter conditions and data flow requirements. The buffer mode is not fixed but adapts in real-time, transitioning between local and remote buffering strategies to optimize the balance between data integrity, power consumption, and latency based on actual system state.
2Reliability
If data is buffered in remote memory to manage jitter, then data loss is prevented, but latency increases
Solution Approach 1:
The memory buffer is segmented into two distinct types: local buffer and remote buffer. The local buffer handles high-speed data transfer with minimal latency for manageable jitter, while the remote buffer provides capacity for larger jitter events. This segmentation allows the system to use appropriate buffer types for different jitter conditions, avoiding the need to always use power-intensive remote buffering.
Solution Approach 2:
The system dynamically switches between local and remote buffer modes based on the current jitter conditions and data flow requirements. The buffer mode is not fixed but adapts in real-time, transitioning between local and remote buffering strategies to optimize the balance between data integrity, power consumption, and latency based on actual system state.
3Reliability
If a large remote memory buffer is used to manage jitter, then data loss is prevented, but device complexity increases
Solution Approach 1:
The memory buffer is segmented into two distinct types: local buffer and remote buffer. The local buffer handles high-speed data transfer with minimal latency for manageable jitter, while the remote buffer provides capacity for larger jitter events. This segmentation allows the system to use appropriate buffer types for different jitter conditions, avoiding the need to always use power-intensive remote buffering.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor buffer occupancy, data flow rates, and jitter conditions to automatically determine when to switch between local and remote buffer modes. This feedback-driven adaptation eliminates the need for complex manual buffer management configurations, reducing device complexity while maintaining data integrity.
4Ease of manufacture
If data streaming uses fixed buffer mode, then implementation is simple, but adaptability to varying jitter levels is poor
Solution Approach 1:
The system dynamically switches between local and remote buffer modes based on the current jitter conditions and data flow requirements. The buffer mode is not fixed but adapts in real-time, transitioning between local and remote buffering strategies to optimize the balance between data integrity, power consumption, and latency based on actual system state.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor buffer occupancy, data flow rates, and jitter conditions to automatically determine when to switch between local and remote buffer modes. This feedback-driven adaptation eliminates the need for complex manual buffer management configurations, reducing device complexity while maintaining data integrity.
Data Source
AI summary
Technologies for low-latency data streaming include a computing device having a processor that includes a producer and a consumer. The producer generates a data item, and in a local buffer producer mode adds the data item to a local buffer, and in a remote buffer producer mode adds the data item to a remote buffer. When the local buffer is full, the producer switches to the remote buffer producer mode, and when the remote buffer is below a predetermined low threshold, the producer switches to the local buffer producer mode. The consumer reads the data item from the local buffer while operating in a local buffer consumer mode and reads the data item from the remote buffer while operating in a remote buffer consumer mode. When the local buffer is above a predetermined high threshold, the consumer may switch to a catch-up operating mode. Other embodiments are described and claimed.