Vehicular Network Rate Adaptation for Connectivity Robustness
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Solution Overview
Problem
Current communication networks are inadequate for supporting complex arrays of both moving and static nodes, such as those found in the Internet of Moving Things, as they fail to provide robust, scalable, and efficient connectivity and services to mobile and static devices.
Innovation Solution
A communication network architecture that is dynamically configurable, using a multi-network on-board unit (OBU) with long-range communication protocols like 802.11p, and a shared context-aware rate adaptation management entity (SME) to adapt parameters for optimal performance in varying environments, ensuring connectivity and services are always-on, secure, and energy-efficient.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current communication networks are used to support mobile and static nodes, then basic connectivity is provided, but the network fails to provide robust, scalable, and efficient connectivity for complex arrays of moving and static nodes
Solution Approach 1:
The patent implements dynamic rate adaptation mechanisms where the SME continuously monitors communication conditions and adjusts transmission parameters in real-time based on network state changes, enabling the network to adapt to varying mobility patterns and environmental conditions
Solution Approach 2:
The system changes communication parameters such as data rate, modulation scheme, and transmission power dynamically based on detected network conditions, allowing the network to optimize performance across different scenarios involving mobile and static nodes
2Productivity
If communication parameters are fixed, then network simplicity is maintained, but performance optimization in varying environments is prevented
Solution Approach 1:
The SME autonomously monitors communication conditions, evaluates performance metrics, and adjusts transmission parameters without external intervention, enabling the system to self-optimize while managing complexity internally
Solution Approach 2:
The system implements feedback loops where communication outcomes are monitored and used to inform subsequent parameter adjustments, creating a closed-loop control system that continuously optimizes performance based on actual results
3Area of stationary object
If long-range communication protocols like 802.11p are used, then connectivity range is extended, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts transmission power and protocol selection based on actual communication needs and distance, using higher power and long-range protocols only when necessary rather than continuously, thereby reducing overall energy consumption while maintaining extended coverage capability
Solution Approach 2:
The SME changes communication parameters including transmission power level, data rate, and protocol type adaptively based on network conditions and energy availability, optimizing the balance between coverage area and energy consumption
Data Source
AI summary
Systems and methods that use adaptive control of communication protocol parameters in a network of moving things. Each network device may share information identifying communication protocol parameters used by the network device through periodic broadcasts, which may be received by neighboring network devices that are within communication range. The neighboring network devices may then adjust their own communication protocol parameters accordingly when attempting to communicate with the first network device and their own neighboring network devices. Network devices that have not received the shared information may use information about their geographic location and the geographic location of neighboring network devices to estimate values of some communication protocol parameters that will provide more effective communication.