Pervasive mobile computing frame based on state middleware

Abstract

The invention discloses a pervasive mobile computing frame based on state middleware. The pervasive mobile computing frame comprises a physical layer, a state server layer and an intelligent service layer. A state server realizes information exchange within a system, and defines the standard for interfaces of the upper layer intelligent service and lower layer physical equipment. A sensor device acquires physical environment information, and updates the information in fixed format on a real-time basis to the state server layer. The state server updates the signals acquired by the physical equipment and provides access interface for the information to the intelligent server layer. The intelligent service layer comprises a plurality of intelligent businesses, requires data from the state server according to the business requirements, and completes intelligent business service . For different state server layers the sensor layer and the intelligent service layer only need to follow specific interfaces. The actual physical equipment or intelligent service types could be any form. Different assemblies of the system can be called through RESTful API. The pervasive mobile computing frame is worth of promoting in actual use.

Description

Technical field [0001] The present invention relates to the technical field of pervasive computing, in particular to a pervasive mobile computing framework based on state middleware. Background technique [0002] Pervasive computing refers to the seamless integration of computing devices into reality to provide users with required services "invisibly" without user input. Realizing ubiquitous computing requires computing devices to actively collect environmental information, obtain environmental information through sensors or other sources, and fuse relevant information together to form context-sensitive information. This related technology is called context awareness or context awareness. In addition, expressing contextual information in an appropriate manner enables the computer to not only process contextual information accurately, but also to perform logical operations such as fusion and recursion on different contextual information to generate new contextual information neede...

AI Technical Summary

Problems solved by technology

However, previous research did not address the following issues well:

The types of sensors, service content, and executable operations are very different, and the acquisition of contextual information is facing great challenges

[0005] 2. Large number of visits and high real-time requirements

[0006] 3. Smart business may become very complex

[0007] 4. High requirements for expansion performance

[0008] 5. Practical promotion issues

Most of the existing designs are simply formulating technical solutions, expecting more users to follow the standard and join in, but ignoring the motivation of users to join, it is not feasible to promote

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