Multiple Transport Channels for Remote Content Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Remote computing systems typically use a single transport channel optimized for one class of data delivery, which can lead to unmet delivery constraints for other data types, resulting in a negative user experience due to inconsistent throughput and delayed data delivery.
Innovation Solution
Implementing multiple transport channels between the client and server, each adapted to efficiently communicate specific data types based on their characteristics and link conditions, with the ability to continuously adjust resources and channel characteristics according to changing network conditions and data requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single transport channel is used for all data elements, then the system complexity is reduced and ease of operation is improved, but the delivery constraints for different data types cannot be met simultaneously, resulting in negative user experience
Solution Approach 1:
The patent divides the single transport channel into multiple specialized channels, each optimized for specific data types (e.g., display data channel, input data channel, clipboard data channel). This segmentation allows each channel to meet the delivery constraints of its designated data type while maintaining manageable system complexity through structured organization.
Solution Approach 2:
The transport channel system is designed with multi-functionality, where channels can be dynamically allocated and reconfigured based on data type requirements. The system provides universal data transmission capability across multiple specialized channels, allowing a single channel infrastructure to serve multiple data delivery purposes simultaneously.
2Productivity
If a single transport channel optimized for one data class is used, then the throughput for that specific data type is improved, but the delivery of other data types experiences delays and constraint violations
Solution Approach 1:
By segmenting the transport system into multiple channels dedicated to specific data types (display data, input data, clipboard data), each channel can be optimized for its specific data class without compromising other data types. This eliminates the time loss experienced by non-optimized data types in a single-channel system.
Solution Approach 2:
Each transport channel is configured with local quality optimization tailored to its specific data type requirements. For example, display data channels may be optimized for high throughput with relaxed ordering requirements, while input data channels may prioritize low latency and strict ordering. This local optimization ensures high productivity for each data type without sacrificing delivery timing for others.
3Reliability
If multiple transport channels are implemented for different data types, then the delivery optimization for each data type is improved, but the device complexity increases
Solution Approach 1:
The multiple transport channels share a common underlying infrastructure and control mechanism, providing universal data transmission capabilities across different channel types. This multi-functionality allows the system to achieve reliable delivery for multiple data types while avoiding the complexity of completely separate transmission systems for each data type.
Solution Approach 2:
The patent merges the control and management functions of multiple channels into a unified system architecture. The transport stack manages multiple specialized channels through a common interface and coordination mechanism, reducing the operational complexity that would otherwise arise from managing entirely independent channel systems.
4Stability of the object's composition
If resources are statically allocated among transport channels, then the system stability is improved, but the adaptability to changing network conditions deteriorates
Solution Approach 1:
The resource allocation among transport channels is made dynamic rather than static. The system continuously monitors network conditions and data delivery requirements, adjusting channel resources in real-time to optimize performance. This dynamic allocation maintains system stability through controlled adaptation rather than rigid fixed assignments.
Solution Approach 2:
The transport system incorporates feedback mechanisms that monitor delivery performance and network conditions, using this information to adjust resource allocation among channels. This feedback-driven approach allows the system to adapt to changing conditions while maintaining stable operation through incremental, controlled adjustments rather than abrupt changes.
Data Source
AI summary
In various embodiments, methods and systems are disclosed for the implementation of multiple transport channels between the client and server. Each of the channels may be adapted to efficiently communicate data for a particular data type and thus be particularly well suited for its data-element characteristics and the detected link characteristics between the client and server.