Multipath Scheduler Lookup Table Interface Selection
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Solution Overview
Problem
Current wireless communication technologies face challenges in efficiently selecting and managing data interfaces with multiple options, leading to suboptimal performance and resource wastage due to unpredictable changes in interface conditions and power consumption, especially in mobile terminals where low latency and low power consumption are crucial.
Innovation Solution
A multipath scheduler is implemented using a lookup table that defines action rules based on weighted performance measures of available data interfaces, enabling adaptive scheduling and seamless transfer between interfaces to optimize resource usage and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional interface selection methods are used, then device complexity is reduced, but throughput and performance efficiency deteriorate due to inability to adapt to changing interface conditions
Solution Approach 1:
The system pre-calculates and stores optimal scheduling decisions in a lookup table before runtime. The lookup table contains pre-computed mappings from interface states to optimal actions, allowing the scheduler to make decisions by simple table lookup rather than complex real-time computation, thus achieving high throughput without real-time computational complexity
Solution Approach 2:
The multipath scheduler automatically monitors interface conditions, determines optimal paths, and adjusts routing decisions without external intervention. The system self-adapts to changing network conditions by continuously updating interface state weights and querying the lookup table, eliminating the need for manual configuration or complex external control mechanisms
2Productivity
If real-time interface monitoring and adaptation is implemented, then performance efficiency is improved, but power consumption increases due to continuous measurement and decision-making
Solution Approach 1:
The optimization problem is solved in advance and results are stored in a lookup table. During runtime, the scheduler only needs to query the pre-computed table based on current interface states, avoiding continuous complex computations and significantly reducing power consumption while maintaining real-time performance efficiency
Solution Approach 2:
The system performs full optimization calculations only when necessary (e.g., when interface conditions change significantly or lookup table needs updating), rather than continuously. Between updates, simple lookup operations are used, reducing overall computational load and power consumption while maintaining adequate performance efficiency
3Adaptability or versatility
If multiple data interfaces are continuously monitored and switched between, then adaptability to changing conditions is improved, but latency increases due to switching overhead and decision-making time
Solution Approach 1:
Optimal routing decisions are pre-computed and stored in the lookup table before runtime. When interface conditions change, the scheduler quickly queries the pre-prepared table to find the optimal path, avoiding time-consuming real-time optimization calculations and reducing latency while maintaining adaptability
Solution Approach 2:
The system continuously monitors interface conditions and uses this feedback to query the lookup table for optimal routing decisions. The lookup table is updated when interface characteristics change, creating a feedback loop that maintains adaptability without requiring continuous complex computation, thus minimizing latency
4Measurement precision
If complex real-time optimization calculations are performed, then scheduling accuracy is improved, but computational resources and processing time are excessively consumed
Solution Approach 1:
The complex optimization problem is solved in advance and results are cached in a lookup table. During actual scheduling operations, the system performs simple table lookups based on interface states, achieving high scheduling accuracy without consuming significant computational resources in real-time
Solution Approach 2:
Instead of performing complex optimization calculations repeatedly, the system creates a copy of the optimal solution in the form of a lookup table. This pre-computed copy is then referenced multiple times during scheduling operations, achieving accurate scheduling decisions with minimal real-time computational overhead
Data Source
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AI summary
A method for providing a multipath scheduler may include causing generation of a lookup table of action rules defining actions corresponding to respective different states in which each of the states is a weighted description of performance measures associated with a data interface, and enabling utilization of the lookup table at a predefined periodicity during communication in a multipath communication environment to identify a selected data interface among a plurality of available data interfaces based on current performance measures associated with the plurality of available data interfaces. A corresponding apparatus and computer program product are also provided.