Network Energy Optimization Using LAG Traffic and Device Layout
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Solution Overview
Problem
Conventional methods for optimizing network energy consumption in high-capacity networks focus on links and are based on trial and error, failing to consider the device layout and coordination among network devices, leading to sub-optimal energy savings.
Innovation Solution
A network device apparatus that obtains energy profiles and traffic information to optimize component states, coordinating with neighboring devices to adjust components such as boards, chipsets, and ports based on device layout and traffic demand, using distributed algorithms to maximize energy savings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional trial-and-error methods are used to optimize link aggregation, then implementation simplicity is maintained, but energy saving effectiveness deteriorates due to sub-optimal decisions
Solution Approach 1:
The network device autonomously determines which components to set to low-power state by evaluating its own energy profile and traffic information, without requiring external control or trial-and-error adjustments. The device self-optimizes by identifying components whose power state can be reduced while maintaining traffic requirements.
Solution Approach 2:
The optimization process uses feedback from traffic information and energy profile data to dynamically adjust component power states. The device continuously monitors traffic demands and energy consumption patterns, using this feedback to make informed decisions about which components should be in low-power state.
2Loss of energy
If only link states are optimized without considering device layout, then implementation simplicity is maintained, but energy saving potential deteriorates due to missed optimization opportunities
Solution Approach 1:
The device is segmented into multiple independent components (boards, chipsets, ports) with distinct power states. The energy profile breaks down total energy consumption into component-level contributions, allowing selective optimization of individual components rather than treating the device as a monolithic unit.
Solution Approach 2:
Different components of the device are treated with different optimization strategies based on their specific characteristics, traffic patterns, and power consumption profiles. Each component's power state is independently determined based on local conditions rather than applying a uniform optimization approach.
3Loss of energy
If network devices operate independently without coordination, then system simplicity is maintained, but overall energy savings deteriorate due to non-optimal network-wide configuration
Solution Approach 1:
Network devices exchange feedback information about their component power states and traffic requirements. This feedback mechanism enables coordinated optimization where each device's decisions consider the state of neighboring devices, allowing the network to converge on an optimal configuration without centralized control.
Solution Approach 2:
The optimization decisions of multiple network devices are merged through coordination protocols. By combining the local optimization decisions of individual devices and resolving conflicts through standardized interactions, the system achieves network-wide energy savings that exceed the sum of independent device optimizations.
4Loss of energy
If additional signaling protocols are implemented for coordination, then energy optimization effectiveness is improved, but system complexity and overhead increase
Solution Approach 1:
The coordination mechanism uses existing, standardized communication protocols and data formats that serve multiple functions in network operations. By reusing established signaling infrastructure for energy optimization purposes, the system avoids creating dedicated complex protocols while still achieving effective coordination between devices.
Data Source
AI summary
The present disclosure relates to energy optimization for links aggregated groups. An apparatus hosted inside a network device is disclosed to coordinate multiple LAGs to turn on/off components of the network device. The apparatus is adapted to decide which components to turn on/off based on a device layout of the network device and coordinate the decision with neighbor network device(s). Thanks to the use of the device layout, a more informed energy optimization decision can be taken. To this end, the apparatus obtains an energy profile of the network device. The energy profile comprises the device layout and energy consumption information associated with each component of the network device. The apparatus further obtains traffic information of the multiple LAGs and optimizes the energy consumption based on the device layout and traffic information. The optimization decision may be coordinated with neighbor network device(s).