Adaptive Zone Allocation for Wireless Backhaul Traffic
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Solution Overview
Problem
Static zone resource allocation in communication networks fails to adapt to varying traffic demands across remote nodes, leading to inadequate resource distribution based on time of day, population activity, and other demand fluctuations.
Innovation Solution
An adaptive zone allocation algorithm that monitors traffic activity periodically and dynamically adjusts zone sizes and resource allocation based on traffic demand, using a weighted round-robin method to prioritize remote nodes with higher traffic needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static zone allocation is used based on number of connected remote nodes, then allocation simplicity and fairness are improved, but adaptability to traffic demand variations deteriorates
Solution Approach 1:
The patent implements dynamic zone allocation by transitioning from static equal partitioning to a dynamic scheme where zone sizes are periodically adjusted based on measured traffic demands. The system continuously monitors traffic at remote nodes and reallocates zones accordingly, making the allocation adaptive rather than fixed.
Solution Approach 2:
The patent changes the allocation parameters from fixed equal shares to variable zone sizes based on traffic demand metrics. By measuring traffic parameters and using them to determine zone allocations, the system adapts resource distribution to actual usage patterns rather than maintaining constant static allocation.
2Device complexity
If static zone allocation is used, then system complexity is reduced, but network performance under varying traffic conditions deteriorates
Solution Approach 1:
The patent introduces feedback mechanisms where traffic demands at remote nodes are measured and fed back to the hub. This feedback loop enables the hub to adjust zone allocations based on actual traffic conditions, improving network performance while maintaining manageable complexity through automated control.
Solution Approach 2:
The system performs self-adjustment by automatically monitoring traffic conditions and reallocating zones without external intervention. The hub autonomously measures traffic demands and modifies allocations based on predefined policies, reducing the need for manual configuration while optimizing performance.
3Ease of operation
If equal resource partitioning among remote nodes is applied, then fairness is improved, but efficiency in handling traffic demand variations deteriorates
Solution Approach 1:
The patent applies local quality by customizing zone allocations to match individual remote node traffic characteristics. Instead of uniform equal partitioning, each node receives zones proportional to its actual traffic demand, optimizing resource efficiency while maintaining fairness through demand-based allocation.
Solution Approach 2:
The system changes allocation parameters from fixed equal shares to variable proportions based on measured traffic demands. By continuously adjusting zone sizes according to actual usage patterns, the system achieves both efficiency in resource utilization and fairness in demand-based distribution.
Data Source
AI summary
Methods and systems for adaptively allocating resources within a communication network, such as adaptive zone allocation in a wireless backhaul network.