Multi-Channel Network Traffic Allocation Using Modern Portfolio Theory
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Solution Overview
Problem
Current communication networks inefficiently allocate resources based on Service Level Agreements and geographical location, leading to large variations in traffic flow, resulting in low network efficiency and potential saturation due to congested or idle channels.
Innovation Solution
Implementing a method that uses modern portfolio theory to optimize network usage parameters by calculating the mean and variance of traffic data, allocating users' traffic to minimize variance within and between channels, and partitioning traffic across multiple channels to balance load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources are allocated based on Service Level Agreement and geographical location with fixed granularity, then service quality is maintained, but network efficiency decreases and channels become congested or idle
Solution Approach 1:
The patent implements dynamic resource allocation that adjusts channel assignments in real-time based on actual traffic conditions and user behavior patterns, moving away from static SLA-based allocation. This allows the system to respond to changing network conditions, balancing service quality maintenance with improved overall network efficiency by dynamically optimizing channel utilization.
Solution Approach 2:
The system changes the allocation parameters from fixed SLA-based rules to variable parameters including user behavior analysis, traffic flow patterns, and channel utilization metrics. This enables flexible adjustment of resource distribution to match actual network conditions, resolving the contradiction between maintaining service quality and improving network efficiency.
2Reliability
If traffic is allocated to dedicated media with fixed granularity, then service level agreement is met, but traffic flow variations cause channel congestion or idle capacity
Solution Approach 1:
The patent segments traffic flows and channel capacities into flexible units that can be dynamically reallocated. Instead of fixed dedicated media assignments, the system divides resources into smaller allocatable units that can be redistributed based on actual traffic demands, reducing both congestion and idle capacity while maintaining SLA compliance.
Solution Approach 2:
The system creates a universal resource allocation framework that can serve multiple users and services across different channels simultaneously. By making channel resources multi-functional and shareable based on real-time conditions rather than dedicated assignments, the system reduces complexity in managing channel utilization while meeting diverse service level requirements.
3Ease of operation
If users' behavior is not taken into consideration in resource allocation, then allocation simplicity is maintained, but large traffic flow variations occur leading to network saturation
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically monitors user behavior patterns and dynamically adjusts resource allocation without manual intervention. This maintains operational simplicity while improving network throughput by using automated behavioral analysis to optimize traffic flow distribution across channels based on actual usage patterns.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor user behavior, traffic patterns, and channel utilization. This feedback drives automatic adjustments to resource allocation, maintaining simplicity of operation while significantly improving network throughput by responding to actual conditions rather than static rules.
Data Source
AI summary
The present disclosure generally relates to apparatus, software and methods for managing multi-channel network traffic to alleviate congestion, improve service quality and make efficient use of channel capacity. The disclosed apparatus, software and methods alleviate congestion and improve service quality by minimizing variance within a channel and/or increase overall traffic flow by minimizing the variance between channels. One or both of these objectives can be accomplished using modern portfolio theory to optimize at least one network usage parameter based on the mean and variance of the parameter(s).