ECN Bits for Intelligent Wireless Network Selection
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Solution Overview
Problem
Current communication networks lack the ability to intelligently select wireless access networks based on real-time congestion conditions, as explicit congestion notification (ECN) data is primarily used at the provider-side cellular network devices and not at user-side mobile devices or non-cellular networks.
Innovation Solution
Extending the use of ECN data to mobile devices and non-cellular networks, allowing them to receive and utilize congestion information to intelligently select the least congested network for data transmission, thereby improving network selection and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If ECN data is used only at provider-side cellular network devices, then network control and management is simplified, but network selection intelligence and user experience are degraded
Solution Approach 1:
The patent introduces an intermediary mechanism where ECN bits in IP packets serve as carriers of congestion information. These bits act as a mediator between the cellular network (provider-side) and non-cellular networks (Wi-Fi), enabling intelligent network selection without requiring complex changes to existing ECN infrastructure. The mobile device reads ECN bits from incoming packets and uses this information to make autonomous network selection decisions.
Solution Approach 2:
The patent extends the functionality of ECN data beyond its traditional use for rate limiting in cellular networks. By enabling mobile devices to read and interpret ECN bits for network selection purposes, the same ECN mechanism serves multiple functions: congestion control in cellular networks and intelligent network selection across multiple access types, thereby improving versatility without adding separate signaling systems.
2Adaptability or versatility
If ECN data is extended to mobile devices and non-cellular networks, then network selection intelligence is improved, but implementation complexity and platform changes increase
Solution Approach 1:
The patent enables mobile devices to autonomously make network selection decisions by reading ECN bits from incoming IP packets. The device's network selection module independently processes ECN information and determines whether to switch between cellular and non-cellular networks without requiring complex external control systems or coordinated changes across multiple network infrastructure components.
Solution Approach 2:
The patent leverages existing ECN bit parameters in IP packet headers, which are already standardized and widely deployed. By reusing these existing parameters for network selection purposes rather than introducing new signaling parameters or protocols, the implementation complexity is minimized while achieving intelligent network selection functionality.
3Productivity
If real-time congestion information is utilized for network selection, then data throughput and user experience are enhanced, but information processing requirements increase
Solution Approach 1:
The patent extracts only the essential congestion information from ECN bits in IP packet headers, rather than processing complete network status reports or extensive signaling data. This extraction approach allows mobile devices to obtain real-time congestion indicators with minimal processing overhead, enabling quick network selection decisions that improve throughput without imposing heavy information processing loads.
Data Source
AI summary
Explicit congestion notification (ECN) bits that have traditionally been utilized in end to end congestion mitigation can be redefined to identify and compare congested and uncongested wireless accesses. Accordingly, mobile devices or other user equipment can leverage ECN data in order to make intelligent network selection, e.g., selecting a network with no congestion over one in a congested state. Accordingly, an application executing at the mobile device can send or receive data via the selected network that is selected based on ECN data.