Network Parameter Adjustment Using Weather Forecasts
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Solution Overview
Problem
Low Power and Lossy Networks (LLNs) face challenges in adapting to varying weather conditions, which affect network performance and application traffic profiles, particularly in Smart Grid Advanced Metering Infrastructure (AMI) networks, where power outages require low-latency and broadcast communication, and existing solutions do not effectively prioritize notifications and restoration during inclement weather.
Innovation Solution
The method involves dynamically adjusting network parameters using weather forecasts to optimize performance by selecting and adjusting link-layer and network-layer parameters, such as broadcast capacity, link margin thresholds, and energy resource management, based on predicted weather conditions, allowing proactive adjustments before changes occur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network parameters are adjusted dynamically based on weather forecasts, then network performance and reliability are improved, but device complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by receiving and processing weather forecasts before adverse weather conditions occur. Network parameters are adjusted in advance based on predicted weather conditions, allowing the network to proactively prepare for potential disruptions rather than reacting after problems occur. This is evident in the patent where weather forecast data is used to pre-adjust transmission power, data rates, and routing parameters before actual weather events impact network performance.
Solution Approach 2:
The patent introduces an intermediary weather forecast system that mediates between environmental conditions and network operations. Instead of directly monitoring complex network metrics and making adjustments, the system uses weather forecast data as an intermediary indicator to trigger parameter adjustments. This intermediary approach simplifies the decision-making process by using external weather data to infer necessary network configuration changes.
2Reliability
If broadcast capacity and link margin thresholds are increased to ensure 99.999% wireless link availability, then network reliability improves, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts broadcast capacity and link margin thresholds based on predicted weather conditions rather than maintaining static high-reliability settings. During normal weather conditions, the system operates with lower energy consumption parameters. When adverse weather is forecasted, the system dynamically increases broadcast capacity and link margin thresholds to ensure 99.999% availability only when necessary. This dynamic adaptation resolves the contradiction by making reliability parameters variable rather than fixed.
Solution Approach 2:
The patent changes network parameters (transmission power, data rates, modulation schemes) based on weather forecast conditions. Instead of maintaining constant high-power transmission for 99.999% availability, the system adjusts these parameters according to predicted weather conditions. During favorable conditions, lower power and less robust modulation are used, conserving energy. During adverse conditions forecasted by weather data, the system transitions to higher power and more robust parameters to maintain availability.
3Loss of time
If low-latency forwarding is prioritized for power outage notifications, then response time improves, but network traffic management complexity increases
Solution Approach 1:
The system applies different quality levels of service to different types of traffic based on weather conditions and application requirements. Power outage notifications receive prioritized low-latency forwarding with guaranteed resource allocation during adverse weather conditions, while other traffic types receive standard service. This local quality differentiation allows critical notifications to achieve low latency without requiring complex end-to-end traffic management for all network flows.
Solution Approach 2:
The patent extracts critical power outage notification traffic from the general network traffic flow and handles it through a separate prioritized path. By separating this critical traffic class, the system ensures low-latency forwarding for notifications without requiring complex traffic management mechanisms for the entire network. The extraction of critical traffic allows simplified handling of the majority traffic while guaranteeing performance for essential notifications.
Data Source
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AI summary
In one embodiment, network parameters are dynamically adjusted using weather forecasts. The embodiments include determining a weather forecast that predicts a weather condition proximate to a network. Network parameters are then selected for adjustment based on the predicted weather condition. The selected network parameters are adjusted to improve performance of the network in response to the predicted weather condition.