Network Routing Scoring for Power Consumption Optimization
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Solution Overview
Problem
Traditional cost-only routing algorithms in large-scale networks ignore power usage, leading to energy inefficiency, as they fail to gather and utilize power consumption data consistently, preventing intelligent routing decisions for energy efficiency.
Innovation Solution
An apparatus and method that incorporate power consumption data into routing decisions using a scoring system (S=α*Cost+β*Consumption), where α and β are coefficients to weight cost and energy efficiency, allowing for the optimization of data paths and placement of redundant network elements into hibernation mode for reduced power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional cost-only routing algorithms are used, then routing decisions are simple and fast, but energy efficiency deteriorates as power consumption is ignored
Solution Approach 1:
The routing algorithm incorporates power consumption as an additional parameter alongside traditional cost metrics. The scoring function S=α*Cost+β*PowerConsumption dynamically evaluates paths based on both cost and energy efficiency, allowing the system to optimize for energy without completely redesigning the routing architecture.
Solution Approach 2:
A path computation element (PCE) acts as an intermediary that gathers power consumption data from network elements and computes optimized routes. This intermediary component handles the complexity of multi-parameter optimization, shielding the core routing logic from unnecessary complexity while enabling energy-efficient routing decisions.
2Loss of energy
If power consumption data is gathered and used in routing decisions, then energy efficiency improves, but data collection and processing complexity increases
Solution Approach 1:
Network elements report their power consumption status to the path computation element, creating a feedback loop. This feedback mechanism enables the system to continuously monitor and respond to power consumption conditions, allowing dynamic routing optimization based on real-time energy efficiency data without requiring complex manual measurement systems.
Solution Approach 2:
Network elements autonomously report their own power consumption data to the PCE, eliminating the need for external monitoring systems. Each network element serves itself by providing the necessary operational data, simplifying the overall data collection architecture while enabling comprehensive power consumption awareness across the network.
3Reliability
If redundant network elements are kept active for backup, then network reliability improves, but power consumption increases
Solution Approach 1:
The system dynamically adjusts the operational state of redundant network elements based on real-time conditions. Instead of keeping all redundant elements permanently active, the PCE can place them in hibernation mode when not needed and quickly activate them when required, creating a dynamic balance between reliability and energy efficiency.
Solution Approach 2:
The system pre-configures redundant network elements and maintains their readiness through lightweight monitoring rather than full activation. Power consumption data and routing alternatives are prepared in advance, allowing the system to rapidly respond to failures without continuously consuming full power on standby elements.
Data Source
AI summary
In an embodiment, the disclosure includes an apparatus comprising a data store which comprises cost data associated with use of a path in a communications network. The data store also comprises power consumption data associated with the use of the path. The apparatus further comprises at least one processor configured to determine a score for the path based on the cost data and the power consumption data. The disclosure also includes an apparatus comprising a path computation element (PCE) configured to receive data from a plurality of network elements (NEs). The data comprises cost and power consumption data for establishing a path between a plurality of the NEs. The PCE is configured to determine a score for the path based on the cost and power consumption data.