Network Energy Optimization via Device Grouping and Parameter Normalization
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Solution Overview
Problem
Existing communication networks face challenges in accurately and reliably evaluating the sustainability of network devices due to inconsistent energy parameter reporting, which can lead to interruptions in connectivity when attempting to optimize energy usage.
Innovation Solution
The implementation of a network optimization logic that discovers network devices, determines device parameters, retrieves placement data, and groups devices into energy management groups to optimize energy usage without affecting uninterrupted connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional sustainability techniques rely on energy parameters to operate network devices in power-saving mode, then energy consumption is reduced, but connectivity interruptions occur
Solution Approach 1:
The system applies different power management strategies to different network devices based on their individual capabilities, hardware characteristics, and roles in the network. Each device is evaluated separately to determine whether it can enter power-saving mode, allowing energy reduction for suitable devices while maintaining connectivity for critical devices.
Solution Approach 2:
The system dynamically adjusts power-saving mode operation based on real-time network conditions and device capabilities. The controller continuously monitors device status and modifies power management decisions to balance energy consumption with connectivity requirements, transitioning devices between operational states as needed.
2Measurement precision
If energy parameters are obtained after network devices capture them, then accurate energy data is collected, but data inconsistency and reporting delays occur
Solution Approach 1:
The system implements a feedback mechanism where the controller requests energy parameters from network devices at specific intervals and uses this information to make real-time power management decisions. The feedback loop ensures that energy data is collected systematically and used to adjust device operation dynamically.
Solution Approach 2:
The system proactively collects energy parameters from network devices before making power management decisions, rather than reacting after devices have already consumed energy. This allows the controller to plan power-saving operations in advance and coordinate device transitions to minimize connectivity impact.
3Loss of energy
If legacy devices are operated in power-saving mode to reduce energy consumption, then energy efficiency improves, but network functionality is compromised
Solution Approach 1:
The system evaluates each legacy device's specific capabilities and hardware characteristics to determine its suitability for power-saving mode. Devices with critical functions or insufficient capabilities are excluded from power-saving operation, while other devices can enter low-power states, allowing energy reduction without compromising essential network functionality.
4Adaptability or versatility
If different network devices report energy parameters in different formats and time intervals, then device compatibility is maintained, but sustainability evaluation accuracy deteriorates
Solution Approach 1:
The controller acts as an intermediary that receives energy parameters from various network devices in different formats and time intervals, normalizes this data into a consistent structure, and uses it for unified sustainability evaluation. This mediation layer preserves device compatibility while enabling accurate comparative analysis of energy consumption across the network.
Data Source
AI summary
Devices, networks, systems, methods, and processes for optimizing the energy consumption of a communication network are described herein. A network optimizer can group multiple network devices in the communication network into one or more energy management groups. The network optimizer may optimize an energy consumption of the one or more energy management groups by generating and transmitting one or more energy optimization configurations. The network optimizer can generate a device replacement list for an energy management group to suggest one or more replacement devices for every replaceable device that is not capable of implementing an energy optimization function. The network optimizer may provide an interactive dashboard and may further facilitate a network operator to modify the energy management groups through the interactive dashboard. The network optimizer can monitor and control the energy consumption of the energy management groups dynamically, thereby resulting into reduction in the energy consumption of the communication network.


