Wireless Control QoS Allocation Based on Agent Survival Time
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Solution Overview
Problem
Existing control systems in wireless communication networks struggle to efficiently allocate Quality of Service (QoS) resources based on the actual control requirements of agents, leading to potential packet loss and congestion, which can degrade system performance.
Innovation Solution
A method to dynamically adjust QoS levels based on the survival time of agents, defined as the number of consecutive control command failures an agent can tolerate before entering an emergency mode, by assigning higher QoS levels to agents with shorter survival times and lower levels to those with longer survival times, using a learning-based approach to determine optimal QoS profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If uniform high QoS levels are allocated to all agents, then system reliability is improved, but network congestion and resource waste occur
Solution Approach 1:
The patent applies local quality by allocating different QoS levels to different agents based on their individual survival times and control requirements. Instead of uniform high QoS allocation, each agent receives a customized QoS level that matches its specific needs, thereby maintaining system reliability where necessary while avoiding network resource waste in other areas.
Solution Approach 2:
The patent changes the QoS parameter allocation dynamically based on agent survival time. The QoS level is adjusted according to the calculated survival time of each agent, transforming from a static uniform allocation to a dynamic parameter-based allocation that optimizes both reliability and resource efficiency.
2Productivity
If QoS levels are reduced to save network resources, then network efficiency is improved, but packet loss increases leading to control degradation
Solution Approach 1:
The patent uses parameter changes by dynamically adjusting QoS levels based on agent survival time calculations. This ensures that QoS is reduced only when and where it can tolerate packet loss without affecting control reliability, thereby improving network efficiency while maintaining necessary control standards.
Solution Approach 2:
The patent applies dynamics by making QoS allocation adaptive and time-varying. The QoS level for each agent is dynamically adjusted based on its current survival time, allowing the system to respond to changing network conditions and agent requirements, thus balancing network efficiency with control reliability.
3Duration of action of stationary object
If fallback commands are used to handle packet loss, then system continuity is maintained, but control performance degrades
Solution Approach 1:
The patent applies preliminary action by calculating and preparing fallback commands in advance based on the agent's survival time. The fallback commands are pre-computed to ensure system continuity during packet loss events, while the QoS allocation is optimized to minimize the frequency of fallback usage, thereby maintaining control precision.
4Productivity
If learning-based QoS allocation is implemented, then resource optimization is improved, but system complexity increases
Solution Approach 1:
The patent applies self-service by implementing a learning-based mechanism that automatically determines optimal QoS levels for each agent based on observed survival times and network conditions. The system self-adjusts QoS allocation without requiring manual configuration, thereby achieving resource optimization while managing complexity through automated learning.
Data Source
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AI summary
It is proposed to request an adapted level of Quality of Service "QoS" for a given agent, wirelessly connected through a telecommunication network to a controller to perform a task. This task is performed by applying successive control commands received from the controller and based at least on sensed data successively received by the controller. The requested QoS level can be chosen in a list proposing a plurality of different QoS levels (QoS#1, QoS#2, QoS#3, QoS#4, QoS#5), ordered from a highest QoS level (QoS#1) to a lowest QoS level (QoS#5). A survival time is determined for said given agent at a current time, said survival time being defined as number of consecutive control commands not applied by the agent due to communication failure with the controller, and that the agent can afford before going into an emergency mode. The number of QoS levels proposed in the list (QoS#1 , QoS#2) depends on the survival time (ST=3), the lower the survival time is, and the lower the number of proposed QoS levels is, the list being reduced, depending on the survival time, by removing the lowest QoS levels (QoS#3, QoS#4, QoS#5) from the list.