Selective Policy Deployment in Mobile Networks
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Solution Overview
Problem
Mobile network congestion is challenging to manage effectively due to the high resource consumption required to track device locations accurately, especially in congested areas, leading to a tradeoff between location accuracy and network resource usage.
Innovation Solution
A method that adjusts the 'stability' interval for determining device locations, allowing devices to report stability only after a configurable time, reducing unnecessary signaling and conserving network resources, while applying appropriate network management policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If devices continuously report location to track device locations accurately in congested areas, then location accuracy is improved, but network resource consumption increases
Solution Approach 1:
The system dynamically adjusts the location reporting behavior based on device stability. Stable devices report location periodically or on-demand, while transient devices report only when stability criteria are met. This dynamic adaptation resolves the contradiction by optimizing reporting frequency according to actual device behavior patterns rather than using a fixed reporting mechanism for all devices.
Solution Approach 2:
The system changes the parameter of location reporting frequency based on device stability classification. By introducing stability thresholds and time-based criteria, the system transforms the binary choice between continuous and no reporting into a graduated approach where reporting frequency is adjusted according to how long a device has remained in the congested area, thereby balancing accuracy needs with resource conservation.
2Measurement precision
If devices report location frequently to maintain accurate tracking, then location tracking accuracy is improved, but signaling demand increases aggravating network congestion
Solution Approach 1:
The system segments devices into stable and transient categories based on their presence duration in congested areas. This segmentation allows differential location reporting strategies: stable devices use standard reporting mechanisms while transient devices use reduced reporting. By dividing the device population into distinct groups, the system maintains accurate tracking for devices that need it while minimizing signaling from devices that are merely passing through.
Solution Approach 2:
The system applies partial location tracking action to transient devices by only reporting when stability criteria are met, rather than continuous reporting. This partial action is sufficient to identify and manage transient devices appropriately without generating excessive signaling demand, thereby resolving the contradiction between tracking accuracy and signaling overhead.
3Reliability
If the system tracks all devices continuously to enforce network management policies, then policy enforcement capability is improved, but network resource usage increases
Solution Approach 1:
The system applies different quality levels of location tracking to different devices based on their stability classification. Stable devices receive full tracking attention with periodic location updates, while transient devices receive minimal tracking only when they meet stability thresholds. This local quality differentiation ensures that policy enforcement resources are concentrated on devices that are actually present and need management, rather than wasting resources on transient devices.
Solution Approach 2:
Devices self-classify as stable or transient based on their own presence duration in congested areas, eliminating the need for continuous network-mediated tracking decisions. The device autonomously determines when to report location based on local stability criteria, reducing network resource usage while maintaining adequate policy enforcement capability through distributed intelligence.
Data Source
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AI summary
Systems and methods described herein employ techniques for optimized and selective management of policy deployment/delivery to mobile clients in a congested network to, for example, prevent further aggravation of network congestion. In order to address mobile network congestion it is necessary to be able to enforce network management policies on the devices which are specifically in the congested areas. This presents a challenge as the process of knowing and keeping track of where a device is geographically located within the network actually consumes network resources. There is a tradeoff between the accuracy with which you know a given devices location and the amount of resources required to gain this knowledge. Thus, it is crucial to have a way to determine the location of a device in the network with sufficient accuracy such that congestion management policies can be applied effectively while not unduly taxing the network with additional traffic.