CN111711674B

CN111711674B - Cloud computing method based on Internet of things

Info

Publication number: CN111711674B
Application number: CN202010506557.8A
Authority: CN
Inventors: 李双印; 赵淦森; 罗浩宇; 王欣明; 邓大权
Original assignee: South China Normal University
Current assignee: South China Normal University
Priority date: 2020-06-05
Filing date: 2020-06-05
Publication date: 2023-03-14
Anticipated expiration: 2040-06-05
Also published as: CN111711674A

Abstract

The invention discloses a cloud computing method based on the Internet of things, which divides a task into a plurality of subtasks through Map Reduce, each subtask acquires required metadata, the method firstly establishes mapping for the acquired metadata, deletes the mapped metadata, only reserves a pure data part, then encapsulates the pure data part, and carries out next processing for the encapsulated data. The method can effectively acquire the required content in the metadata by copying and deleting the metadata, avoids the interference of invalid links, address pointers and the like, eliminates the influence of viruses or hackers, is favorable for the safe use of the data, and can realize the safe and reliable application of the data.

Description

Cloud computing method based on Internet of things

Technical Field

The invention relates to a preparation process of an Internet of things, in particular to a method for realizing safe data intercommunication of the Internet of things through cloud computing.

Background

The Internet of Things (The Internet of Things, IOT for short) is used for collecting any object or process needing monitoring, connection and interaction in real time through various devices and technologies such as various information sensors, radio frequency identification technologies, global positioning systems, infrared sensors and laser scanners, collecting various required information such as sound, light, heat, electricity, mechanics, chemistry, biology and position of The object or process, realizing wide connection of The object and The person through network access, and realizing intelligent sensing, identification and management of The object and The process. The internet of things is an information bearer based on the internet, a traditional telecommunication network and the like, and all common physical objects which can be independently addressed form an interconnected network. At present, the internet of things is widely applied to a plurality of fields such as existing video monitoring, home safety monitoring and intelligent transportation.

Cloud computing (cloud computing) is one type of distributed computing, and refers to decomposing a huge data computing processing program into countless small programs through a network "cloud", and then processing and analyzing the small programs through a system consisting of a plurality of servers to obtain results and returning the results to a user. By the technology, tens of thousands of data can be processed in a short time (several seconds), so that strong network service is achieved.

Therefore, the internet of things is actually a system for acquiring and managing basic data, the cloud computing is a system for processing data, the cloud computing stores data and information in a distributed manner, and the distributed manner stores data in a redundant manner. Cloud computing service providers often have extremely large entrance bandwidth and a large number of edge access nodes, sensor data distributed in various places can be uploaded to the edge nodes of the cloud service providers conveniently and quickly, and then the sensor data are transmitted to a computing center through a high-speed network by the edge nodes, so that the delay of data transmission is greatly reduced, and the timeliness of data processing is improved, so that the cloud computing service providers and the edge nodes are naturally combined together.

However, privacy is stolen in cloud computing security, data in cloud computing is often open and is easily attacked by hackers, so that the operation of cloud computing is unknown, and meanwhile, loss is large, and loss caused by loss of data cannot be predicted. In cloud computing, a large number of users store data in the cloud computing, and even a person with no particular significance illegally obtains information through the cloud computing, viruses are implanted into the data in the cloud computing, and the viruses can not only cause that a computer taking the cloud computing as a carrier cannot work normally, but also can be copied and spread through some ways, so that great harm is brought to the internet, and therefore, improvement is brought to security of the cloud computing urgently.

Disclosure of Invention

Therefore, in view of the problems in the prior art, the main object of the present invention is to provide a cloud computing method based on the internet of things, which directly eliminates data with errors and possibly hidden viruses through the acquisition and analysis of cloud computing data, thereby achieving the safety and reliability utilization of data.

The invention further aims to provide the cloud computing method based on the internet of things, and the method further achieves the aim of safe acquisition by closing all data transmission contents such as external links in the data without judging the authenticity and reliability of the data.

Based on this, the invention is realized as follows:

a cloud computing method based on the Internet of things divides a task into a plurality of subtasks through Map Reduce, each subtask acquires required metadata, mapping is firstly established on the acquired metadata, the mapped metadata is deleted, only a pure data part is reserved, then the pure data part is packaged, and the packaged data is processed in the next step. Here, mapping refers to copying metadata and creating corresponding mapping metadata, so that the metadata is processed to avoid influence on original data. The method can effectively acquire the required content in the metadata by copying and deleting the metadata, avoids the interference of invalid links, address pointers and the like, eliminates the influence of viruses or hackers, is favorable for the safe use of the data, and can realize the safe and reliable application of the data.

Furthermore, the mapping is performed through Map functions, one Map function corresponds to a part of original data, and the mapping operation is performed on the part of original data. The maps are independent, so that the maps can be fully parallelized, and the efficiency is improved.

Further, after mapping, a merging operation is performed on a part of the intermediate results generated by each Map through the Reduce function. Because Reduce is independent of each other, the simple concatenation of the final results produced form the complete result set.

Further, the method removes descriptive contents such as identification (e.g. identification code, key, etc.), type, authority, address, attribute, date, etc. when deleting the data format, and only retains the pure data portion.

Furthermore, for the pure data part, all link addresses and fields for sending data in the pure data part are deleted before being sealed and stored, so that the reliability and the non-transferability of data contents are ensured, and the invasion or diffusion of viruses or hackers is avoided.

Alternatively, the link in the pure data section, the field to send the data, is set to disable access.

Furthermore, for the structured data, namely the data with fixed format and limited length, the head and tail contents of the mapped metadata are deleted in a targeted manner.

Furthermore, for unstructured data, due to the fact that unstructured data is not of a fixed length and is not of a fixed format, the unstructured data content needs to be identified, and data portions and descriptive contents such as identification, type, authority, address, attribute, date and the like need to be distinguished.

Further, for the encapsulation of the pure data part, a C + + virtual function is adopted under the general condition, so that the utilization rate and convenience of data can be improved.

The invention has the following technical effects:

the invention can effectively acquire the required content in the metadata by independently copying and deleting the metadata, avoids the interference of invalid links, address pointers and the like, eliminates the influence of viruses or hackers, is favorable for the safe use of the data and can realize the safe and reliable application of the data.

Drawings

FIG. 1 is a flow chart of an implementation of the present invention.

Detailed Description

In order to more clearly describe the present invention, a specific implementation of the present invention is further described below with reference to the accompanying drawings.

The applicant finds that an important channel for hacker or virus propagation is realized by copying and external linking, that is, for a certain program or data, the hacker or virus can only complete intrusion or virus diffusion by controlling the program to generate data read-write operation, and if the read-write mode of the data is isolated, the hacker intrusion or virus diffusion can be avoided. As shown in fig. 1, in order to implement the cloud computing method based on the internet of things, the method first obtains metadata, and for the obtained metadata, the method first establishes mapping, where mapping refers to copying the metadata and establishing corresponding mapping metadata, so that the metadata is processed to avoid influence on original data; and then deleting the mapped metadata, only reserving a pure data part, packaging the pure data part, and carrying out next processing on the packaged data.

The method comprises the following specific steps:

101. acquiring metadata, dividing a task into a plurality of subtasks through Map Reduce, and acquiring the required metadata by each subtask;

102. mapping, namely, mapping the acquired metadata, wherein the mapping is established firstly, and the mapping refers to copying the metadata and establishing corresponding mapping metadata, so that the metadata is processed, and the influence on original data is avoided;

the mapping is carried out through Map functions, one Map function corresponds to a part of original data, and the mapping operation is carried out on the part of original data. The maps are independent, so that the maps can be fully parallelized, and the efficiency is improved.

After mapping, merging operation is carried out on a part of intermediate results generated by each Map through Reduce functions, and because Reduce is mutually independent, the generated final results are simply connected to form a finished result set.

103. Deleting metadata, for mapped data, removing descriptive contents such as identification (such as identification code, key and the like), type, authority, address, attribute, date and the like, and only keeping a pure data part.

Meanwhile, all the link addresses and the fields for sending data in the pure data part are deleted, or the link addresses and the fields for sending data in the pure data part are set to be access-forbidden. Therefore, the read-write operation of other external linked software on the data can be effectively avoided, the reliability and the non-transferability of the data content are ensured, and the invasion or the diffusion of viruses or hackers is avoided.

And for the structured data, namely the data with a fixed format and a limited length, the head and tail contents of the mapped metadata are deleted in a targeted manner.

For unstructured data, due to the fact that unstructured data is not of a fixed length and is not of a fixed format, unstructured data content needs to be identified, and data portions and descriptive contents such as identification, type, authority, address, attribute and date need to be distinguished.

104. Packaging data, namely packaging the pure data part according to the language required by a user in a normal condition; based on the universality and universality of C + + language application, a C + + virtual function is generally adopted, so that the utilization rate and convenience of data can be improved.

105. And (6) ending.

The encapsulated data can be directly used for subsequent other operations or processing.

In a word, the invention acquires the metadata independently, can effectively acquire the required content in the metadata by copying and deleting the metadata, avoids the interference of invalid links, address pointers and the like, purifies the data content, eliminates the influence of viruses or hackers, is beneficial to the safe use of the data, and can realize the safe and reliable application of the data.

The foregoing is illustrative of the embodiments of the present invention and the technical principles employed, and it is within the scope of the present invention that the resulting functional effects may vary without departing from the spirit of the present invention as embodied in the specification and drawings.

Claims

1. A cloud computing method based on the Internet of things is characterized in that mapping is established for the acquired metadata, the mapped metadata are deleted, only a pure data part is reserved, then the pure data part is packaged, and the packaged data is processed in the next step;

the mapping is carried out through Map functions, one Map function corresponds to a part of original data, and the mapping operation is carried out on the part of original data;

after mapping, merging a part of intermediate results generated by each Map through a Reduce function;

when the data format is deleted, the method removes the explanatory content and only keeps the pure data part;

for the pure data part, deleting all link addresses and fields for sending data in the pure data part before packaging;

setting the link in the pure data part and the field for sending data as access prohibition;

for structured data, namely data with a fixed format and a limited length, deleting the head and tail contents of the mapped metadata in a targeted manner;

for unstructured data, as the unstructured data are data with indefinite length and unfixed format, the unstructured data content needs to be identified to distinguish the data part from the explanatory content;

and the pure data part is encapsulated by adopting a C + + virtual function, so that the utilization rate and convenience of data can be improved.