Adaptive Inactivity Timer for Mobile Network Signaling Reduction
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Solution Overview
Problem
Frequent transitions between idle and active states in user devices lead to unnecessary signaling and resource allocation/de-allocation, burdening both user devices and communication towers, reducing battery life and impacting network efficiency.
Innovation Solution
Identifying idle state patterns in user devices to set device-specific inactivity time durations and using deep packet inspection to capture transition data, which helps in minimizing unnecessary transitions by aligning detection periods with user device patterns and identifying applications or devices causing excessive signaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed inactivity time duration is used for all user devices, then network resource management is simplified, but unnecessary transitions between idle and active states occur frequently, burdening both user devices and communication towers
Solution Approach 1:
The patent applies local quality by transitioning from a uniform inactivity time duration applied to all user devices to device-specific inactivity time durations. Each user device receives a customized inactivity time duration based on its individual transition patterns, allowing the system to adapt to different device behaviors and reduce unnecessary state transitions for specific devices while maintaining simplified management through automated pattern learning.
2Measurement precision
If deep packet inspection is performed on all data packets, then transition data can be captured accurately, but network processing load and latency increase
Solution Approach 1:
The system performs preliminary actions by learning and storing transition patterns for user devices in advance. Once patterns are learned, the network can make intelligent decisions about when to perform deep packet inspection without needing to inspect all packets continuously. This allows accurate transition data capture only when necessary, reducing overall processing load while maintaining measurement precision.
Solution Approach 2:
The patent implements self-service by having the network automatically learn and adapt to each user device's transition patterns without manual configuration. The system self-adjusts the inactivity time duration for each device based on observed behavior, eliminating the need for manual intervention or overly broad inspection policies, thus balancing accuracy with processing efficiency.
3Loss of energy
If inactivity time duration is extended to reduce transitions, then battery life is conserved, but legitimate active states may be missed, reducing detection precision
Solution Approach 1:
The patent applies dynamics by making the inactivity time duration adaptive rather than static. The system continuously monitors user device behavior and adjusts the inactivity time duration dynamically based on observed transition patterns. This allows the parameter to extend when appropriate to conserve battery life while shortening when necessary to maintain detection precision, optimizing both objectives simultaneously.
Data Source
AI summary
Systems, methods, and computer-readable media, for reducing transitions between active and idle states are provided. In some embodiments, transition data indicating transitions between an active state and an idle state associated with a mobile device is received. Thereafter, an idle state pattern that indicates a pattern of an idle state associated with the mobile device is identified. Based on the idle state pattern, an inactivity timer update corresponding with the idle state pattern is provided to at least one communication tower. The inactivity timer update provides a time duration or time duration adjustment to be applied by the at least one communication tower for use in detecting a transition from an active state to an idle state.