Dynamic Node Cluster Discovery via Probabilistic Message Forwarding
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Solution Overview
Problem
Current communication systems face challenges in dynamically discovering and managing node clusters within networks, particularly in efficiently selecting cluster leaders based on varying parameters and metrics, which affects network performance and service reliability.
Innovation Solution
The system employs a method where nodes send discovery messages with headers and visited object blocks containing node information, allowing them to determine cluster leaders based on degree, member count, and latency metrics, and rank potential leaders to select the most suitable cluster leader, while also updating and forwarding these messages randomly within the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If nodes use multiple parameters (degree, member count, latency) to select cluster leaders, then cluster formation quality improves, but the complexity of leader selection increases
Solution Approach 1:
The patent applies parameter changes by normalizing multiple cluster leader selection parameters (degree, member count, latency) to a common scale. Each parameter is normalized independently to eliminate unit differences and enable fair comparison. The normalized parameters are then combined into a composite score that determines cluster leader selection, resolving the contradiction by transforming complex multi-parameter evaluation into a standardized single-metric decision process.
2Adaptability or versatility
If discovery messages are forwarded randomly throughout the network, then cluster discovery coverage improves, but message propagation time increases
Solution Approach 1:
The patent implements periodic action through the time-to-live (TTL) mechanism in discovery messages. Each message carries a TTL counter that decrements with each hop, automatically limiting propagation depth and duration. This creates periodic discovery waves that cover the network systematically without indefinite propagation, balancing discovery coverage against propagation time by allowing messages to traverse the network in controlled intervals rather than continuously.
3Measurement precision
If nodes continuously update and forward discovery messages, then cluster discovery accuracy improves, but network traffic overhead increases
Solution Approach 1:
The patent applies partial action by having nodes selectively update and forward discovery messages based on specific conditions rather than continuously. Nodes compare received discovery messages against their local knowledge and only regenerate/forward messages when they contain new or improved information (e.g., better cluster leader candidates, updated parameter values). This partial updating approach maintains discovery accuracy by propagating meaningful changes while avoiding redundant traffic from continuous message regeneration.
Data Source
AI summary
Various example embodiments for supporting dynamic node cluster discovery in a communication network are presented. Various example embodiments for supporting dynamic node cluster discovery in a communication network may be configured to support dynamic node cluster discovery based on circulation of discovery messages within the communication network. Various example embodiments for supporting dynamic node cluster discovery based on the circulation of discovery messages within the communication network may be configured to support dynamic node cluster discovery based on probabilistic forwarding of discovery messages within the communication network. Various example embodiments for supporting dynamic node cluster discovery based on the circulation of discovery messages within the communication network may be configured to support dynamic node cluster discovery based on updating and forwarding of discovery messages within the communication network. Various example embodiments for supporting dynamic node cluster discovery in a communication network may be configured to support dynamic, multi-level node cluster discovery.