Access Point Selection Using Historical Patterns
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Solution Overview
Problem
Current WLAN technologies face challenges in efficiently managing client device access points, particularly in selecting the optimal access point for client devices based on historical usage patterns and future scheduled events, leading to potential performance degradation due to random selection of home agents and increased latency.
Innovation Solution
Implement a system that selects an access point for client devices based on historical usage patterns and future scheduled events, using data encryption tunnels and selection logic to ensure efficient network access and minimize latency by pre-configuring the selected access point for services such as IP address assignment and data forwarding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If random selection of home agents is used for client device access, then device complexity is reduced, but network performance degrades due to increased latency and packet loss
Solution Approach 1:
The system performs preliminary actions by analyzing historical usage patterns and future scheduled events to pre-determine the optimal access point for client devices before actual connection occurs. This advance preparation enables the network to proactively configure selected access points for services such as IP address assignment and data forwarding, thereby reducing latency and packet loss during actual device connection while maintaining manageable complexity through automated selection logic.
2Reliability
If historical usage pattern analysis is implemented for access point selection, then network performance improves, but system complexity increases due to data collection and processing requirements
Solution Approach 1:
The system implements a multi-functional architecture where a single controller performs diverse functions including historical usage pattern analysis, future scheduled event processing, access point selection, and network configuration. This universal approach consolidates multiple specialized components into one integrated system, thereby improving access point selection accuracy through comprehensive data analysis while controlling overall system complexity through functional consolidation rather than proliferation of separate systems.
3Loss of time
If pre-configuration of selected access points is performed, then latency is reduced for client device connection, but processing time and computational resources increase
Solution Approach 1:
The system employs periodic action by analyzing historical usage patterns and future scheduled events at intervals rather than continuously, and by pre-configuring access points only for devices with predicted future connections. This approach reduces connection latency for targeted devices through selective pre-configuration while conserving computational resources by avoiding continuous monitoring and processing for all devices, thereby optimizing the balance between speed and energy consumption.
Data Source
AI summary
A method includes selecting a particular access point for performing service corresponding to a client device that is associating or associated with a different access point. The particular access point is selected based on historical usage pattern and/or a future scheduled event corresponding to the client device.