Multi-sensor Internet of Things resource adaptive deployment management and control middleware

Abstract

Multi-sensor Internet of Things resource adaptive deployment management and control middleware is designed and constructed, and data dynamic decision is made based on environment close calculation; middleware is designed to realize fusion access deployment of various wireless communication network nodes; through virtualization of attributes and processing of sensor nodes in a sensing network, a virtual sensor abstract pool is formed in a middleware platform, and implementation details of heterogeneous sensing nodes and a communication protocol are shielded; according to the design, a real-time dynamic management and control message publishing and subscribing process of an application end in the aspects of node resource discovery and deletion, node running state monitoring, node working modes and the like is realized, and end-to-end interaction between a sensor node and the application end is realized; data filtering and calculation are added in the middleware, interconnection and intercommunication between different devices of the sensor network are achieved, the problem that heterogeneous network information nodes are difficult to fuse and transmit is solved, sensing layer devices and data types are more diversified, and the requirements of various industries in the future are better met.

Description

technical field [0001] The present application relates to a middleware for sensor Internet of Things deployment management and control, in particular to a multi-sensor Internet of Things resource self-adaptive deployment management and control middleware, which belongs to the technical field of Internet of Things middleware. Background technique [0002] With the development of wireless sensor networks and mobile Internet, as well as the emergence of cloud computing technology, the Internet of Things has been widely deployed in various applications such as environmental monitoring, smart home, smart agriculture, and urban traffic control. It integrates intelligent perception, digital identity, ubiquitous network and cloud computing technologies, and connects terminal sensing devices with the Internet to achieve comprehensive perception and intelligent services. The Internet of Things includes embedded electronic devices, software, sensors, and communication networks. These o...

AI Technical Summary

Problems solved by technology

The current application layer cannot capture these frequent network status changes in a timely manner, and make corresponding observation records and remote control. The existing technology uses manual configuration for remote observation to manage resources. It is not only time-consuming and laborious, but also difficult to achieve. Real intelligent observation cannot achieve intelligent observation and dynamic deployment management and control. It lacks an access platform that can dynamically adapt to various node resources, lacks resource configuration information and data information encapsulation abstraction, and cannot observe network operations while efficiently responding to various network operations in real time. Various resource access and status changes and other issues, lack of fault location and node operation status monitoring mechanism, can not promptly and effectively detect node work failures and abnormal working modes in the sensing network, and the cost of deploying and maintaining the sensing network is high

[0011] (3) In the current wireless sensor network monitoring environment, the network management and control are complicated, the nodes fail intermittently, and the sensor networks in different application scenarios lack effective rapid and dynamic deployment methods. The Internet of Things nodes based on multi-sensor network fusion observation Resource management and control lacks improvements in node resource identification, resource registration update, node working mode control, and node operating status feedback. Supports simultaneous access to node resources of four typical heterogeneous wireless communication networks ZigBee, Bluetooth, WiFi, and 6Lowpan. It does not integrate resource management and MQTT protocol-based message agent functions, and cannot realize the complementary advantages of common wireless sensing networks. The reusability and scalability of the network are poor, and the application layer cannot manage and control node resources end-to-end intelligently and transparently. It lacks the pre-analysis and calculation of all sensing data inside the edge device of the Internet of Things, and cannot utilize higher value The observation data is transmitted to the application side, the cost of data transmission and the energy consumption of the device in the process of transmitting data are large, and the delay of application decision-making is long

[0012] (4) The current Internet of Things middleware is still concentrated in the underlying perception and interconnection, and there is a big gap in the realization of high flexibility, reusability, and high reliability of Internet of Things applications; the complexity of Internet of Things applications is low , the scale is still in its infancy, and IoT applications that support large-scale device access still have many problems that need to be overcome, such as heterogeneous physical device integration, service quality control, complex event processing, security and access control, and the workload of operation and control is heavy. Functions such as connection between the underlying network and the application layer and the integration of task-required programming interfaces cannot be realized. IoT terminal resources are limited, energy is limited, and nodes are highly heterogeneous. The middleware solution is not lightweight in terms of performance and cannot In response to the characteristics of the management and control requirements of various heterogeneous node resources, the middleware itself is not high in hardware performance and cannot carry a large amount of data forwarding tasks. It lacks the edge analysis and processing of data into the middleware functional modules, and cannot play the role of middleware in The role of linking the preceding and the following in the IoT architecture

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