Remote WLAN Power Proxy for Multi-Client Energy Scheduling
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Solution Overview
Problem
Current technologies lack effective methods for optimizing energy usage among multiple mobile devices by efficiently scheduling shared WLAN bandwidth, as existing techniques are not designed to handle multiple clients or provide necessary information about client configuration and state, leading to conflicts and suboptimal energy savings.
Innovation Solution
A remote network-connected computer, acting as a power-aware proxy, probes wireless clients to determine their configuration and state, including beacon reception times, intervals, and timeout intervals, to facilitate transitions between power save and active modes, and schedules wireless traffic based on these parameters to reduce energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If existing power management techniques are used for single client, then power savings can be achieved for that client, but these techniques cannot be extended to multiple clients and cause conflicts when multiple clients share WLAN bandwidth
Solution Approach 1:
The patent segments the power management function by introducing a dedicated power management entity that separates power management responsibilities from individual client applications. This entity independently manages power settings for multiple clients without requiring changes to client software, resolving the conflict between single-client optimization and multi-client applicability.
Solution Approach 2:
The patent introduces a power management entity as an intermediary between the WLAN system and mobile devices. This intermediary collects information about client configurations and states, then makes centralized power management decisions that optimize energy savings across multiple clients simultaneously, avoiding the conflicts that arise when each client independently applies power management techniques.
2Use of energy by moving object
If more information about client configuration and state is collected to optimize power management, then better energy savings can be achieved, but the complexity of the system increases
Solution Approach 1:
The patent extracts the complex information collection and analysis functions from individual clients and concentrates them in a dedicated power management entity. This entity gathers necessary information about client configurations and states through standardized interfaces, then processes this information centrally to make power management decisions, reducing the complexity burden on individual devices while enabling sophisticated power optimization.
3Productivity
If WLAN bandwidth is shared among multiple mobile devices, then more devices can communicate with the network, but efficient scheduling to reduce energy consumption is not provided by existing techniques
Solution Approach 1:
The patent implements dynamic power management by continuously monitoring client states, traffic patterns, and network conditions. The power management entity dynamically adjusts power settings and traffic scheduling based on real-time information, optimizing the balance between network capacity utilization and energy consumption for each client at any given moment.
Solution Approach 2:
The patent establishes feedback loops where the power management entity continuously collects information about client configurations, states, and network performance. This feedback is used to iteratively refine power management decisions and traffic scheduling, ensuring that energy consumption is optimized while maintaining adequate network capacity for multiple devices.
Data Source
AI summary
To conserve energy, components in mobile devices have to transition less frequently between “active” and “sleep” modes, and to sleep for longer intervals. In accordance with at least one preferred embodiment of the present invention, there is broadly contemplated herein an approach for remote discovery of wireless client and access point configurations, especially those settings associated with the power consumption of the client's wireless interface. Methods contemplated in the preferred embodiment use packet probing techniques to determine the client and access point configurations remotely. The probing techniques include sending packets to the client device, over the wireless LAN, at intervals calculated using data publicly available on the wireless LAN technology in use and results of previous packet probing measurements. Measurements from several packet probes and methods for statistical data processing are used to make a determination.