Method and system for prefetching and pushing node data in Internet of Things system

Abstract

The invention relates to a method and a system for prefetching and pushing node data in an Internet of Things system. The method comprises the following steps of: S1, determining an interaction frequency statistical table of each node in an nth period; s2, performing calculation according to the interaction frequency statistical table to obtain a demand association degree table and a service association degree table between any two nodes; and S3, in the (n + 1) th period, according to the demand association degree table and the service association degree table, pre-fetching and pushing data among the nodes. According to the invention, data pre-fetching or pushing is carried out on the nodes in the Internet of Things system in a targeted manner, so that the working efficiency of the nodes is improved, and the task processing time delay is reduced.

Description

technical field [0001] The invention relates to the technical field of the Internet of Things, in particular to a method and system for prefetching and pushing node data in an Internet of Things system. Background technique [0002] Inside the communication chip protocol layer operating system, the common message push modes are user request-based push and active push; the message push strategy based on user request belongs to the traditional information interaction mode. The target node sends a request message, the target node responds to the request after receiving the message, and the requesting node parses the response message after receiving it, and extracts valid data, thus completing a data request-push process; the strategy idea Intuitive, easy to implement, suitable for embedded devices with low computational complexity, but does not consider bandwidth utilization and network node working status. If the requested data is not required by the current task, the real-tim...

AI Technical Summary

Problems solved by technology

This push strategy is still not flexible enough. A more obvious defect is that if the network environment or the status of the server node itself fluctuates frequently, a large amount of actively pushed data will be generated, which will occupy more network bandwidth. A large amount of data is pushed, and the demand side node stores or replaces the original data after receiving the data, which increases the workload

If the demand side node does not need this data temporarily, the storage of data may also cause a large amount of storage space to be occupied

This push strategy that does not consider the needs of demand-side nodes is very likely to cause waste of CPU computing resources and network bandwidth resources of demand-side nodes

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