Energy-Aware Mobile Policy Control for Greener Network Slices
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Solution Overview
Problem
The ICT industry's high electricity consumption and variable carbon intensity from renewable energy sources pose challenges in designing eco-friendly communication policies that account for temporal and spatial dimensions of energy sources, making it difficult to reduce carbon footprint effectively.
Innovation Solution
Implementing enhanced policy control mechanisms in mobile communications that utilize energy-related information to generate UE, AM, and SM policies, guiding UEs to route traffic through 'greener' network slices based on time and location criteria, and adjusting resource allocation for eco-friendly network resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the network provides comprehensive policy control for all applications, then the ability to manage carbon footprint is improved, but the system complexity increases
Solution Approach 1:
The patent segments the policy control system by application type and energy characteristics. Different policy control mechanisms are applied to different application categories (e.g., real-time communication vs. non-real-time), allowing the system to manage carbon footprint selectively without overwhelming complexity across all services.
Solution Approach 2:
The system dynamically adjusts policy parameters based on energy-related information such as carbon intensity, renewable energy ratio, and time of day. By changing policy parameters (QoS levels, routing decisions) in response to varying energy conditions, the system achieves adaptable carbon management without requiring permanent complex configurations.
2Adaptability or versatility
If the network dynamically adjusts policies based on real-time energy information, then carbon intensity optimization is improved, but the response time and processing overhead increase
Solution Approach 1:
The network pre-configures multiple policy templates and QoS profiles that can be rapidly deployed when energy conditions change. Instead of creating policies from scratch in real-time, the system selects and activates pre-prepared policy configurations, significantly reducing response time while maintaining optimization capability.
Solution Approach 2:
The system implements dynamic policy adjustment mechanisms that automatically respond to changing energy conditions without requiring manual intervention. Policies are continuously adapted based on real-time energy information, allowing the network to optimize carbon intensity while maintaining acceptable response times through automated decision-making.
3Adaptability or versatility
If the network routes all traffic through greener network slices, then renewable energy utilization is improved, but the quality of service for time-sensitive applications deteriorates
Solution Approach 1:
The patent applies different quality attributes to different traffic flows based on their specific requirements. Time-sensitive applications receive policies that prioritize low latency and guaranteed bandwidth, while non-real-time applications can utilize greener network slices with optimized energy parameters. This localized quality differentiation allows renewable energy utilization without compromising real-time service reliability.
Solution Approach 2:
Instead of routing all traffic through greener network slices, the system applies green routing selectively to portions of traffic that can tolerate energy optimization trade-offs. By applying the action partially to only suitable applications and traffic types, the system maximizes renewable energy utilization while preserving QoS for critical real-time communications.
4Measurement precision
If the network collects and processes detailed energy-related information from multiple sources, then the accuracy of carbon footprint calculation is improved, but the information processing complexity and data requirements increase
Solution Approach 1:
The patent introduces an energy information collection and processing intermediary layer that aggregates data from multiple sources (grid operators, renewable energy providers, network elements) into unified energy profiles. This intermediary layer simplifies the complexity by pre-processing and normalizing data before it reaches the policy control functions, reducing the burden on individual network elements while maintaining calculation accuracy.
Solution Approach 2:
The system employs a universal energy information processing framework that handles multiple data types and sources through a single standardized mechanism. The same processing architecture serves various purposes including carbon footprint calculation, renewable energy ratio determination, and QoS optimization, reducing overall system complexity through multi-functionality.
Data Source
AI summary
Various solutions for enhanced policy control with energy-related information in mobile communications are described. An apparatus may receive energy-related information from at least one network function (NF). Then, the apparatus may generate at least one of a user equipment (UE) policy, an access and mobility (AM) policy, and a session management (SM) policy for an apparatus based on the energy-related information. Also, the apparatus may provide the at least one of the AM policy, the SM policy, and the UE policy to the apparatus.