Decentralized Beacon Scheduler for P2P Mesh Network Collision Avoidance
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Solution Overview
Problem
In peer-to-peer (P2P) or mesh networks, persistent collisions of beacon frames transmitted by different Information Handling Systems (IHSs) can occur, especially when IHSs are from the same manufacturer, leading to inefficiencies and potential failures in concurrent collaboration sessions.
Innovation Solution
The implementation of a decentralized Wi-Fi beacon frame scheduler that intelligently orchestrates and schedules beacons in P2P or mesh networks, using Multicast Collaboration Beacons (MCBs) configured based on contextual information such as collaboration session details and network conditions, to avoid collisions and optimize network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If beacon frames are transmitted at fixed time intervals by multiple IHSs in a P2P or mesh network, then network discovery and session establishment are enabled, but persistent beacon collisions occur leading to network inefficiency and session failures
Solution Approach 1:
The system performs preliminary scheduling of beacon transmission times before actual transmission occurs. The decentralized beacon scheduler pre-calculates and assigns specific time slots to different IHSs based on their network identifiers and current network conditions, preventing collisions before they happen. This preliminary coordination allows multiple IHSs to transmit beacons reliably without conflicts.
Solution Approach 2:
The beacon transmission schedule is made dynamic rather than static. The decentralized scheduler continuously adjusts transmission times based on real-time network conditions, detected beacon collisions, and changing collaboration session requirements. This dynamic adaptation allows the system to maintain high reliability while optimizing network efficiency under varying conditions.
2Adaptability or versatility
If multiple concurrent collaboration sessions are supported in a P2P or mesh network, then network versatility and user productivity are enhanced, but beacon collisions become more frequent and severe
Solution Approach 1:
The system segments the beacon transmission space by creating dedicated time slots and frequency channels for different collaboration sessions. The decentralized scheduler divides the network into multiple logical groups, each with its own beacon transmission parameters. This segmentation allows multiple concurrent sessions to operate simultaneously without their beacons colliding, maintaining both versatility and reliability.
Solution Approach 2:
The system introduces additional dimensions for beacon differentiation beyond simple time division. By utilizing multiple frequency channels, spatial routing information elements, and session-specific beacon identifiers, the system creates a multi-dimensional beacon space. This allows concurrent collaboration sessions to coexist without interference, enhancing both adaptability and reliability.
3Reliability
If decentralized beacon scheduling is implemented to avoid collisions, then beacon transmission reliability improves, but device complexity and coordination overhead increase
Solution Approach 1:
The decentralized beacon scheduler operates autonomously at each IHS without requiring centralized control or complex inter-device coordination. Each IHS independently determines its beacon transmission schedule based on simple rules involving its network identifier and locally detected beacon collisions. This self-service approach maintains high reliability while minimizing device complexity and coordination overhead.
Solution Approach 2:
The system simplifies the scheduling complexity by changing key parameters to fixed or pseudo-random values derived from IHS identifiers. Rather than requiring complex real-time calculations, each IHS uses predetermined algorithms with fixed parameters based on its unique ID. This parameter standardization reduces computational complexity while maintaining reliable collision-free transmission.
Data Source
AI summary
Systems and methods for beacon orchestration for concurrent collaboration sessions in peer-to-peer (P2P) or mesh networks are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: detect a first multicast collaboration beacon (MCB) in a P2P or mesh network comprising two or more IHSs; identify a first collaboration session between the two or more IHSs based upon the first MCB; and transmit a second MCB configured, based at least in part upon the first MCB, to orchestrate a second collaboration session in the P2P or mesh network.