Communication Controller Common Capacity Ratio Estimation
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Solution Overview
Problem
Existing communication systems face challenges in determining an optimal common capacity ratio for upstream and downstream communication channels, leading to potential traffic starvation due to rate adaptation techniques and the inability to accurately reflect fair apportionment of capacity across links.
Innovation Solution
A communication controller estimates expected upstream and downstream traffic flows using a common capacity ratio, defining a utility function to maximize fairness and configure capacities accordingly, ensuring ingress rates converge to a fair working point without requiring deep packet inspection or relying on observable traffic combinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If rate adaptation techniques are applied by source nodes, then traffic flows adjust to available capacity, but observed ingress rates do not accurately reflect fair apportionment of capacity
Solution Approach 1:
The system performs preliminary estimation of the number of traffic flows before determining capacity allocation. By estimating flow counts in advance (N_d,l and N_u,l), the system can calculate fair capacity apportionment based on expected flow characteristics rather than relying solely on observed ingress rates that are distorted by rate adaptation. This preliminary action enables the controller to set capacity ratios that achieve fair apportionment despite source nodes applying rate adaptation techniques.
2Measurement precision
If deep packet inspection is used to determine traffic flows, then accurate traffic classification is achieved, but system complexity and processing overhead increase
Solution Approach 1:
The invention extracts only the essential information needed for capacity allocation - specifically, the number of traffic flows in each direction - without requiring deep packet inspection. By taking out just the flow count metric (N_d,l and N_u,l) rather than analyzing packet contents, the system achieves sufficient measurement precision for capacity management while avoiding the complexity and processing overhead of deep packet inspection. This extraction approach maintains accuracy where needed while eliminating unnecessary complexity.
3Ease of operation
If common capacity ratio is configured for all communication links, then simplified control is achieved, but inability to adapt to individual link traffic patterns reduces network efficiency
Solution Approach 1:
The system applies local quality by estimating and applying specific capacity ratios (R_com) for each individual communication link based on its local traffic characteristics. Rather than imposing a uniform capacity ratio across all links, the controller determines link-specific ratios by estimating the number of traffic flows (N_d,l and N_u,l) on each link and calculating the ratio that maximizes utility function (3). This enables each link to have optimized capacity allocation tailored to its specific traffic patterns, improving overall network efficiency while maintaining manageable complexity through automated estimation.
Data Source
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AI summary
Example embodiments describe a communication controller (101) comprising means for performing i) estimating expected amounts of upstream and downstream traffic flows on respective communication links having configurable upstream and downstream capacities by means of a common capacity ratio for the communication links; and ii) determining, based on the expected amounts of upstream and downstream traffic flows, a desired common capacity ratio for which expected upstream and downstream ingress rates of the communication links will converge to a working point according to an apportionment of the upstream and downstream capacities to the respective expected amounts of upstream and downstream traffic flows.