Pervasive Computing Operation System with Multi-Agent Context Adaptation
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Solution Overview
Problem
Existing operation and maintenance environments in pervasive computing lack adaptability to dynamically changing context information, leading to inefficiencies in data processing and management.
Innovation Solution
An operation information system based on pervasive computing is developed, incorporating a multi-agent communication system, an information node listener, context retriever, interpreter, decision agent, and execution agent, which utilize a software-defined architecture to manage and process context information through a cloud knowledge base for self-adaptive management and data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a multi-agent communication system is constructed to collect information through multiple agents, then information collection capability is improved, but system complexity increases
Solution Approach 1:
The system divides functionality into multiple independent agents, each responsible for collecting information from specific sensors or data sources. This segmentation allows parallel information collection while maintaining modular architecture, reducing overall system complexity through distribution.
Solution Approach 2:
The multi-agent communication system serves multiple functions: information collection, context awareness, decision support, and system management. By making the system multi-functional, the patent reduces the need for separate specialized systems, thereby managing complexity while enhancing information collection capability.
2Adaptability or versatility
If context information is processed and fused through multiple agents, then adaptability to dynamic context is improved, but processing time increases
Solution Approach 1:
The system performs preliminary processing of context information by agents continuously monitoring and pre-processing data streams. This allows the system to maintain adaptability to dynamic context while reducing real-time processing delays, as pre-processed information is ready for quick integration when needed.
Solution Approach 2:
The multi-agent system implements feedback mechanisms where agents continuously report context changes to the central controller, which adjusts processing priorities and routing in real-time. This feedback loop enables the system to adapt to dynamic context while optimizing processing time by focusing computational resources on the most critical and changing contexts.
3Measurement precision
If high-level deduction is performed through context awareness, then decision-making accuracy is improved, but computational resource consumption increases
Solution Approach 1:
The patent segments the computational workload by assigning different levels of processing to different agents. Simple context collection and basic processing are handled by distributed agents, while complex high-level deduction and decision-making are performed by the central controller. This segmentation reduces overall computational resource consumption while maintaining high decision-making accuracy through specialized processing at each level.
Data Source
AI summary
Provided is an operation information system based on pervasive computing. An information node listener is responsible for listening to a distribution information node and an update of stored context information. A context retriever is responsible for indexing and retrieving the stored context information. An interpreter is configured to provide services for the information node listener and the context retriever. When the context information is retrieved and found out to be changed, a relevant body is configured for self-adaptive management. A fusion processing is performed on the information. A decision agent and an execution agent are configured to manage and control message transfer between agents and provide data for an effector. A network is configured to use a software-defined architecture to transfer data from a sensor platform to a server in a cloud.