Adaptive Network Power Modes for Demand-Based Capacity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional network management systems focus on maximizing capacity and coverage without considering power optimization, leading to unnecessary energy consumption by network components.
Innovation Solution
A decision intelligence-based framework that adaptively configures network hardware to meet current demand by dynamically toggling between operational modes, balancing performance and power savings based on real-time data and behavioral patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network components operate at maximum capacity and coverage, then network performance is improved, but energy consumption increases
Solution Approach 1:
The patent implements dynamic operational modes that allow network components to adjust their performance characteristics in real-time. The system transitions between different operational states (e.g., high-performance mode, energy-saving mode) based on current network conditions and traffic demands, enabling the network to maintain adequate performance while reducing energy consumption during low-utilization periods.
Solution Approach 2:
The system changes operational parameters such as transmit power levels, channel bandwidth, and antenna configuration dynamically. By adjusting these parameters based on actual network needs rather than maintaining fixed maximum settings, the system achieves energy savings while preserving necessary network performance for active users.
2Adaptability or versatility
If network capacity is maximized, then user coverage is improved, but power drain increases
Solution Approach 1:
The system applies partial action by providing network coverage and capacity only to the extent necessary for current user needs. Rather than maintaining maximum capacity across the entire network area continuously, the system dynamically adjusts coverage levels and capacity allocation to match actual utilization patterns, reducing energy waste in underutilized regions.
Solution Approach 2:
The network is segmented into multiple operational zones or functional blocks that can be independently controlled. This allows different portions of the network to operate at different capacity levels simultaneously, with high-capacity operation only where users are actively present and lower-capacity or dormant operation in areas without active users.
3Reliability
If access points operate continuously at full power, then network availability is improved, but energy efficiency deteriorates
Solution Approach 1:
The system implements periodic monitoring and evaluation of network conditions, transitioning access points between active and energy-saving states based on detected usage patterns. During periods of low or no activity, access points can enter sleep modes or reduce transmission power, while automatically activating when user presence or traffic demands are detected, thus maintaining availability while improving energy efficiency.
Solution Approach 2:
The system continuously monitors network utilization, user presence, and performance metrics, using this feedback to dynamically adjust access point operational states. This closed-loop control ensures that network availability is maintained at required levels while energy consumption is optimized by avoiding continuous full-power operation when it is not necessary.
Data Source
AI summary
Disclosed are systems and methods that provide a computerized network management framework that adaptively configures hardware components providing a network at a location based on determined intelligence about the location, including behavioral patterns of users in/around the location. The framework can automatically, in a dynamic manner, trigger and toggle between operational modes of the network so as to provide or offer the necessary network capacity and coverage for current demands on the network. The framework enables a computerized balance between network performance and power savings by configuring the network hardware to operate at power levels specific to the current needs of the network's connected devices. Thus, the disclosed framework provides mechanisms for varying operational modes that meet the threshold needs of network requests, thereby ensuring expected performance of the network is maintained while reducing the power strain on the network components.