Cluster Selection Using Hop Count and Master Rank
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Solution Overview
Problem
Existing wireless communication technologies face challenges in efficiently selecting the optimal cluster for neighbor awareness networking, particularly in determining the best cluster based on signal strength, hop count, and master rank values, which affects network synchronization and data dissemination.
Innovation Solution
A method and apparatus that receive synchronization messages from multiple neighbor awareness network clusters, comparing signal levels, hop counts, and master rank values to select the cluster with the highest master rank and lowest hop count, ensuring efficient network synchronization and data dissemination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cluster selection is based solely on signal strength, then connection reliability is improved, but network synchronization efficiency deteriorates due to ignoring hop count and master rank
Solution Approach 1:
The patent changes the selection parameters from single-criterion (signal strength only) to multi-criterion (signal strength, hop count, and master rank value). This allows the system to evaluate clusters comprehensively, selecting those that optimize both connection reliability and synchronization efficiency by balancing multiple factors rather than prioritizing one parameter.
2Speed
If cluster selection prioritizes low hop count, then data dissemination speed is improved, but connection stability deteriorates due to ignoring signal strength
Solution Approach 1:
The patent introduces a multi-parameter evaluation system that combines hop count, signal strength, and master rank value. This resolves the contradiction by not exclusively prioritizing low hop count but rather finding an optimal balance where data dissemination speed and connection stability are both satisfied through comprehensive cluster evaluation.
3Measurement precision
If multiple parameters are considered for cluster selection, then selection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent implements a self-service mechanism where the wireless device autonomously evaluates multiple parameters (signal strength, hop count, master rank value) and performs cluster selection without requiring complex external coordination. The device uses locally available information from synchronization messages to make selection decisions, reducing overall system complexity while maintaining high selection accuracy.
Data Source
AI summary
Embodiments enable access to a wireless communications medium. In example embodiments, a method comprises receiving first synchronization messages from a wireless device transmitting synchronization messages in a first neighbor awareness network cluster, the first synchronization messages including a first hop count value to a first anchor master in the first cluster and information describing a first master rank value of the first anchor master; receiving second synchronization messages from a wireless device transmitting synchronization messages in a second neighbor awareness network cluster, the second synchronization messages including a second hop count value to a second anchor master in the second cluster and information describing a second master rank value of the second anchor master; and selecting the first neighbor awareness network cluster or the second neighbor awareness network cluster, based on at least one of the first and second hop count values and the first and second master rank values.