Remote Server Rule Generation for Client Device Energy Reduction
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Solution Overview
Problem
Existing data collection systems in sensor networks face challenges in minimizing energy expenditure and adapting behavior of client devices without significant computational or communication complexity, especially when disconnected from the communication infrastructure.
Innovation Solution
The system employs a Remote Correlation and Local Adaptation (RECOLA) architecture, where a remote server analyzes data patterns and contextual information to generate rules that modify the behavior of client devices, including data transmission rates and alert generation, without requiring continuous network connectivity or direct access to all contextual data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If client devices continuously transmit data samples to the remote server, then the server can accurately analyze patterns and generate behavioral rules, but the communication overhead and energy expenditure of client devices increase significantly
Solution Approach 1:
The patent extracts only the most essential data elements for pattern analysis. Instead of transmitting complete data samples, the system identifies and transmits only critical features and anomalies that are necessary for the server to generate accurate behavioral rules, thereby reducing communication overhead while maintaining analysis accuracy.
Solution Approach 2:
The system implements partial action by selectively transmitting data based on predefined criteria and anomaly detection. Client devices monitor local conditions and only transmit data when specific thresholds are exceeded or when behavioral changes are detected, rather than continuously transmitting all data samples.
2Adaptability or versatility
If client devices perform significant computational processing to adapt their behavior locally, then they can respond autonomously when disconnected from the server, but the computational complexity and resource requirements of the client devices increase
Solution Approach 1:
The patent introduces a middleware layer that resides on the client device but operates simple, pre-configured adaptation rules. This intermediary layer enables local behavioral adaptation without requiring complex computational processing, as it follows straightforward decision logic that can be executed on resource-constrained devices.
Solution Approach 2:
The system performs preliminary action by pre-configuring client devices with basic adaptation rules and thresholds before deployment. These pre-established rules enable devices to adapt their behavior locally when disconnected from the server, without requiring complex real-time computational processing or machine learning algorithms on the client side.
3Use of energy by moving object
If the system minimizes communication overhead to reduce energy consumption, then client devices can operate longer on battery power, but the server receives insufficient data to accurately determine patterns and generate behavioral rules
Solution Approach 1:
The patent implements a feedback mechanism where the server sends generated behavioral rules back to client devices. Clients use these rules to guide their data collection and transmission decisions, transmitting data that is most relevant for validating and refining the rules. This feedback loop ensures that minimal data transmission is sufficient to maintain accurate pattern analysis.
Solution Approach 2:
The system dynamically changes transmission parameters based on operational context. Transmission frequency, data sampling rates, and communication intervals are adjusted according to the current operational state, anomaly detection results, and received behavioral rules, allowing the system to minimize communication overhead while ensuring sufficient data is transmitted for accurate pattern analysis.
4Reliability
If client devices transmit detailed contextual information to the server, then the server can generate more accurate and context-aware behavioral rules, but the communication bandwidth requirements and data transmission time increase
Solution Approach 1:
The patent extracts only the most relevant contextual information for rule generation. Instead of transmitting complete contextual datasets, the system identifies and transmits only those contextual parameters that are critical for generating accurate behavioral rules, such as environmental conditions, device state, and operational patterns, thereby reducing transmission time while maintaining rule accuracy.
Data Source
AI summary
Techniques are disclosed for localized adaptation of client devices based on correlation or learning at a remote server. For example, a method for modifying a behavior of a client device (102) in a data collection system (100), wherein the client device collects data and transmits data to a server (108), includes the following steps. The client device transmits (204) data to the server. The server uses at least a portion of the data received from the client device to generate (206) information that represents a modification to a behavior of the client device. The server device transmits (208) the generated information to the client device. The client device subsequently alters the behavior of the client device based on the informatio n received from the server.