Context Profile Management for Reducing Server Load
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Solution Overview
Problem
Context-aware computing systems face excessive system load due to processing redundant context data, leading to increased total cost of ownership (TCO), as servers continually process unchanged data without efficient management mechanisms.
Innovation Solution
A dynamic context data management system that uses context profiles to control data collection and processing, allowing administrators to configure what data to collect, how frequently, and in what format, and applying data processing rules to only process relevant data, thereby reducing redundant data processing and system load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the server processes all received context data from context providers, then the system maintains comprehensive data processing capability, but the system load increases excessively due to redundant data processing
Solution Approach 1:
The patent applies preliminary action by implementing a context data cache that stores previously processed context data before new data arrives. The system compares incoming context data with cached data and only processes new data if it has actually changed. This preliminary comparison mechanism prevents redundant processing of unchanged data, reducing system load while maintaining comprehensive processing capability for actual data changes.
2Duration of action of stationary object
If the server continuously processes context data at fixed intervals, then the system maintains consistent processing rhythm, but redundant unchanged data is processed repeatedly causing excessive system load
Solution Approach 1:
The patent applies dynamics by making the data processing interval adaptive rather than fixed. The system dynamically adjusts the processing rhythm based on whether context data has actually changed. When data changes, processing occurs immediately; when data remains unchanged, processing is skipped. This dynamic approach maintains consistent processing rhythm for actual changes while avoiding energy waste on redundant unchanged data processing.
3Reliability
If the server processes all context data without filtering, then no relevant data is missed, but redundant data processing increases total cost of ownership
Solution Approach 1:
The patent applies the extraction principle by separating relevant context data from redundant data through a caching mechanism. The system extracts only the changed data portions by comparing incoming context data with previously cached data. This extraction approach ensures no relevant data is missed while filtering out redundant unchanged data, thereby reducing operational costs without compromising data completeness.
Data Source
AI summary
A context profile is created. The context profile includes one or more types of context data to be captured, frequency in which the one or more types of context data to be captured, data format in which the one or more types of context data is to be outputted and one or more custom data types. The context profile corresponds to an application identifier. A mapping of context profiles to application identifiers is created. Based on the mapping, the context profile is sent to a corresponding context provider.Upon reception, the one or more types of context data are evaluated. Based on a number of data processing rules, the received context data can be processed or discarded.