Multi-Tier Deterministic Routing via Neural Sub-Path Scoring
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Solution Overview
Problem
Current communication networks face challenges in efficiently managing deterministic flows due to limitations in resource allocation and routing, particularly in multi-tier hierarchical networks, where ensuring bounded performance metrics like latency and jitter is complex.
Innovation Solution
The implementation of a system that uses a sub-path determination agent, supported by a neural network, to select feasible sub-paths for deterministic flows based on scoring, which includes scheduled and candidate sub-path information, resource availability, and performance metrics, ensuring optimal resource allocation and routing within the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional routing methods are used in multi-tier hierarchical networks, then network complexity is reduced, but deterministic performance metrics (latency and jitter) cannot be guaranteed
Solution Approach 1:
The network is divided into multiple tiers with hierarchical routing domains. Each tier handles routing independently, segmenting the complex global routing problem into manageable local routing decisions. This allows deterministic performance to be guaranteed within each tier while avoiding the complexity of centralized global routing.
Solution Approach 2:
Routing paths for deterministic flows are pre-computed and established before actual data transmission. The system performs preliminary routing setup, resource reservation, and path validation to ensure deterministic performance metrics are met before traffic begins flowing, eliminating the need for complex real-time routing decisions.
2Adaptability or versatility
If dynamic resource allocation is implemented for deterministic flows, then network adaptability improves, but resource allocation complexity increases
Solution Approach 1:
The resource allocation system dynamically adjusts routing paths and resource reservations based on real-time network conditions while maintaining deterministic guarantees. The multi-tier architecture enables dynamic adaptation at each tier independently, allowing flexible resource allocation without requiring complex global coordination.
3Productivity
If multi-tier hierarchical routing is implemented, then network scalability improves, but routing decision complexity increases
Solution Approach 1:
The routing decision-making process is segmented across multiple hierarchical tiers. Each tier makes routing decisions independently based on local network state, avoiding the need for complex centralized decision-making. This segmentation enables network scalability while keeping individual routing decisions relatively simple.
Data Source
AI summary
Various example embodiments for supporting multi-tier deterministic networking are presented. Various example embodiments for supporting multi-tier deterministic networking may be configured to support provisioning of deterministic flows in multi-tier deterministic networking. Various example embodiments for supporting multi-tier deterministic networking may be configured to support adaptive deterministic routing in multi-tier deterministic networks. Various example embodiments for supporting multi-tier deterministic networking may be configured to support score-based deterministic routing in multi-tier deterministic networks. Various example embodiments for supporting multi-tier deterministic networking may be configured to support adaptive deterministic routing and/or score-based deterministic routing in multi-tier deterministic networks based on analysis of a state representation for path and/or sub-path selection in multi-tier deterministic networks. Various example embodiments for supporting multi-tier deterministic networking may be configured to support hierarchical resource allocation and deallocation in multi-tier deterministic networking, optimal route finding in multi-tier deterministic networking, and so forth.