Dynamic Link Probing for OLSR Route Selection
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Solution Overview
Problem
Standard Optimized Link State Routing (OLSR) platforms require static configuration of link quality multipliers, which is impractical in emergency situations where network topologies are unknown and need to be set up quickly.
Innovation Solution
A dynamic controlling framework that dynamically optimizes routing selections by measuring and favoring neighboring links with high bandwidth and low latency, using a link probing tool to compute link quality multipliers and update routing decisions in real-time, eliminating the need for prior knowledge of network link characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static configuration of link quality multipliers is used in OLSR platforms, then routing decisions can be made with known network characteristics, but the system cannot adapt to unknown or changing network topologies in emergency situations
Solution Approach 1:
The patent transforms the static link quality multiplier configuration into a dynamic system that automatically adjusts multipliers based on real-time link measurements. The system continuously probes links and updates routing decisions without requiring manual reconfiguration, enabling rapid adaptation to changing network conditions while maintaining optimal performance.
Solution Approach 2:
The system implements self-service by automatically discovering network topology and configuring link quality multipliers without human intervention. The OLSR platform autonomously measures link characteristics, computes appropriate multipliers, and updates routing tables, eliminating the need for administrators to have prior knowledge of network characteristics.
2Reliability
If link quality multipliers are statically configured, then routing optimization can be applied with known link characteristics, but prior knowledge of network link characteristics is required which is impractical in emergency situations
Solution Approach 1:
The system implements feedback by continuously measuring actual link performance through probing tools and using this information to dynamically adjust link quality multipliers. The measured link characteristics feed back into the routing decision process, ensuring that routing optimization remains accurate while eliminating the need for manual configuration knowledge.
Solution Approach 2:
The patent dynamically changes the link quality multiplier parameters based on measured link characteristics such as bandwidth and latency. Instead of using fixed static values, the system adjusts these parameters in real-time according to actual network conditions, maintaining routing optimization accuracy while simplifying operation.
3Productivity
If manual configuration of link quality multipliers is required, then routing decisions can be optimized for known networks, but the complexity of configuring and maintaining these parameters increases
Solution Approach 1:
The system performs self-service by automatically discovering network topology, measuring link characteristics, and configuring link quality multipliers without human intervention. This eliminates the complexity of manual configuration while maintaining routing optimization, enabling rapid network setup in emergency situations.
Solution Approach 2:
The patent introduces a link probing tool as an intermediary that automatically measures link characteristics and provides this information to the routing system. This intermediary handles the complex measurement and computation tasks, simplifying the overall system operation while enabling productivity through automatic configuration.
Data Source
AI summary
A dynamic controlling framework that is adapted to dynamically optimize existing routing decisions in an optimized link state routing (OLSR) platform to favor higher-bandwidth, lower-latency links in the active link database. The dynamic controlling framework includes a link probing tool that is in communication with OLSR platform where the link probing tool is adapted to dynamically measure estimated bandwidth, latency scores, or both estimated bandwidth and latency scores of active links in the active link database of the OLSR platform. The dynamic controlling framework includes a plug-in framework that is in communication with the OLSR platform and the link probing tool where the plugin framework is adapted to receive at least one link quality multiplier (LQM) metric computed by the link probing tool and to combine the at least one LQM metric with the OLSR platform's existing link quality (LQ) metric for enhancing route selection by the OLSR platform.