Network Traffic Prediction for Energy-Saving Device Operation
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Solution Overview
Problem
The rapid expansion of network scale leads to increased energy consumption and operational costs, generating significant carbon emissions.
Innovation Solution
A network device adjusts its running status by predicting future traffic patterns and selecting an energy-saving policy that matches the expected traffic, thereby reducing energy consumption without compromising performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network scale is expanded to meet increasing demand for network services, then network service capacity is improved, but network energy consumption increases
Solution Approach 1:
The patent applies dynamics by enabling network devices to dynamically adjust their running status based on predicted traffic patterns. The controller predicts future traffic and sends adjustment instructions to network devices, allowing them to adapt their energy consumption levels to actual network conditions rather than operating at fixed high-power states continuously.
Solution Approach 2:
The patent implements parameter changes by modifying operational parameters of network devices based on traffic predictions. The controller determines optimal running status parameters (such as processing power, memory allocation, interface states) and configures network devices accordingly, changing these parameters dynamically to match predicted traffic demands and reduce energy consumption during low-traffic periods.
2Reliability
If network device operates at high performance status continuously, then network service quality is maintained, but energy consumption increases
Solution Approach 1:
The patent applies preliminary action by predicting future traffic patterns before they occur and proactively adjusting network device running status in advance. The controller uses historical traffic data and prediction algorithms to forecast upcoming traffic conditions, then pre-configures network devices to appropriate power states, ensuring service quality is maintained when traffic arrives while avoiding unnecessary energy consumption during low-traffic periods.
Solution Approach 2:
The patent implements feedback by continuously monitoring actual traffic conditions and using this information to refine traffic predictions and adjust network device configurations. The system collects traffic data, compares predicted versus actual traffic patterns, and uses this feedback to improve prediction accuracy and optimize energy saving policies, creating a closed-loop control system that balances service quality and energy efficiency.
Data Source
AI summary
A method and an apparatus for adjusting a running status of a network device and a related device are disclosed. A second network device sends, to a first network device, first traffic information of traffic processed by the second network device in a first time period. The first network device predicts, based on the first traffic information, second traffic information corresponding to the second network device in a second time period. The first network device determines, based on the second traffic information, energy consumption corresponding to each energy saving policy, and determines, as a target energy saving policy, an energy saving policy corresponding to energy consumption that meets a preset condition. The first network device sends the target energy saving policy to the second network device, to enable the second network device to be run based on a configuration parameter in the target energy saving policy.