Network-Centric Power Management for Remote Device Anticipation
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Solution Overview
Problem
Conventional power management techniques in computing devices operate autonomously and fail to effectively manage power consumption in networked environments, such as homes and offices, as they do not account for activities initiated by remote users, leading to high power costs due to uncertainty about device usage.
Innovation Solution
A network-centric power management system that monitors and controls device nodes by collecting and processing network-wide data to anticipate user requests and adjust power usage, using communication nodes, control nodes, and device nodes to generate and send power management commands, thereby reducing power consumption while minimizing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If autonomous power management techniques are used, then device can automatically enter power-saving mode based on current activity levels, but it fails to account for activities initiated by remote users leading to high power costs
Solution Approach 1:
The system performs preliminary actions by monitoring activity patterns and predicting future device usage before it actually occurs. The power management system analyzes historical data, user behavior patterns, and scheduled tasks to anticipate when the device will be needed, allowing it to enter power-saving modes proactively while ensuring the device is ready when actually needed by local or remote users.
2Reliability
If device remains powered on to account for remote user activities, then power availability is maintained, but power costs increase due to uncertainty about device usage
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring device usage patterns, user behavior, and activity levels. This feedback loop allows the power management system to learn from actual usage data, refine its predictions, and dynamically adjust power states. The system receives feedback about when devices are actually used by local or remote users and uses this information to improve future power management decisions, reducing unnecessary power consumption while maintaining availability.
Solution Approach 2:
The power management system dynamically adjusts device power states based on real-time and historical data. Instead of static power management policies, the system continuously adapts its behavior by analyzing changing usage patterns, user preferences, and environmental factors. This dynamic approach allows the system to optimize the balance between device availability and power consumption, transitioning between different power states based on predicted and actual usage needs.
3Use of energy by moving object
If network-centric power management is implemented, then power consumption is reduced through intelligent anticipation of user activity, but system complexity increases due to network-wide data collection and processing
Solution Approach 1:
The network-centric power management system is segmented into distributed components, with each device having its own power management agent that operates semi-autonomously. These distributed agents collect local data and make local decisions, while periodically coordinating with a central management system. This segmentation reduces the complexity burden on any single component and allows the system to scale by adding more independent agents without proportionally increasing overall system complexity.
Data Source
AI summary
Disclosed is a method of managing power consumption of a system with a first device coupled to a communication device of a communication network by way of a first communication link and a second device coupled to the communication device of the communication network by way of a second communication link.