In the era of big data and information, the Internet of Things (IoT) has become widely used in daily life, reflecting the rapid development of modern information technology. However, as the volume of data that needs to be processed increases, the issues of real-time data exchange and access have become increasingly prominent, further complicating the data processing in IoT. Based on this, this article discusses the demand for real-time information exchange based on IoT and how this information is exchanged. Finally, it analyzes strategies for real-time information exchange of big data to improve work efficiency, attract a larger audience with a complete processing system, expand the application scope of IoT in various fields of social development, and further promote the development of IoT.
IoT, as it is known, mainly combines computer technology with internet technology to form a new information platform. With the help of corresponding information sensing devices and certain connection methods, it integrates computer IoT with physical objects to create an intelligent and automated information management system. This not only accelerates the exchange and sharing of information but also enables computers to connect to the internet and physical objects. A new connection between information transactions and economic transactions has been established, promoting further development of the social economy. Issues of Massive Real-Time Information Exchange in IoT1. System processing tools cannot function properlyThe background of massive data generation is the rapid development of the internet. Due to the rapid growth of such information and data, IoT has imposed stricter requirements on real-time information processing. This rapid growth puts excessive pressure on the data and information in databases. If there is insufficient space, it will reduce the efficiency of database access. Therefore, the decrease in information transmission efficiency significantly hinders the construction and development of IoT.2. Query functions cannot respond in a timely mannerThe continuous generation of massive data increases the system inventory of the information platform, but each system’s data capacity has certain limitations. Without a scientific plan for implementation, the data information may exceed the corresponding limits, weakening system performance. The increase in data volume leads to difficulties in usage, reducing the system’s response efficiency during statistical queries, resulting in low efficiency in data information processing. Demand Analysis for Massive Data Information Exchange Based on IoT1. Rapid data processing must be achievedInformation exchange mainly refers to the connection between management objects and the computer internet in the form of data, processing data information to achieve the exchange of IoT data and information resources. Before data information exchange, data information must be processed, including data resource compression and data format conversion. In the era of big data, it is necessary to extract useful data information from massive information to ensure the quality of data information. This has become an urgent issue to be resolved in the process of IoT information exchange.2. Data information sharing needs to be realizedThe main purpose of information exchange is to achieve the sharing of data and information resources, improving the utilization efficiency of data resources. In the development of IoT technology, the sharing of data and information resources must first ensure the consistency of data formats and consider the compatibility between various data modules to achieve the sharing of data and information resources. However, the current compatibility of data information modules is relatively poor, and there are no clear data format standards. This is an urgent issue to be resolved for achieving data information resource sharing. Strategies for Massive Real-Time Information Exchange Based on IoT1. It is recommended to use memory-mapped file methodsThe implementation of real-time information exchange of big data in IoT mainly focuses on computer hard drives. The method of accessing file information is through the Winesap function. However, with the advent of the big data era, more and more information resources need to be integrated and processed. This operational method is gradually becoming outdated, and its efficiency is not ideal. In this case, the more complete operational technology of memory-mapped file methods has become a more efficient operational method in IoT. The memory-mapped file method has three core aspects.2. Optimize indexing and caching technologiesThroughout the entire process of real-time information exchange of big data, the functions used by users include querying and accessing, which rely on indexing and caching technologies. Indexing technology can be divided into clustered and non-clustered indexes, both of which have their advantages and disadvantages. In terms of clustered indexing, it can store large databases in an ordered manner. Once the user starts indexing, it will provide information. Other Exchange Query Optimization Strategies1. Caching technologyFor data that does not change within a certain period, is frequently accessed, and does not grow, such as basic information in IoT, caching it on the server allows the client to directly obtain the required data cache from the request. This strategy only returns the data needed for the client to perform operations each time, avoiding the repeated creation, processing, and transmission of data, reducing the number of database accesses, improving the response speed of the client, and enhancing system performance. It can also prevent unexpected stops of the data service system, ensuring data support within a certain period, thus improving system stability and availability. The downside is that the initial query requires a connection to the database to cache data, which is relatively slow.2. Indexing technologyThere are two main indexing technologies: clustered indexing stores table data in index order. Although this indexing technology has higher retrieval efficiency than ordinary indexing, it significantly impacts data insertion, deletion, and modification; non-clustered indexing does not affect the storage order of table data, has lower retrieval efficiency than clustered indexing, but has less impact on data insertion, deletion, and modification. Real-time information in IoT has characteristics such as large data volume, frequent column updates, and frequent revisions of indexed columns. Therefore, it is more suitable to establish non-clustered indexes in database design.3. Database connection pool technologyThe management of database connections clearly affects the scalability and robustness of the entire application system as well as the performance metrics of the program. For the massive data access demands of real-time information in IoT, the traditional method of accessing the database server through JDBC is evidently insufficient. Here, a connection pool can be introduced to improve the performance and concurrency of Java server code that relies on the database. A connection pool is a buffer for database connections located in memory. Connections can be reused through the connection pool without needing to create and cancel each time; at the same time, it can release database connections that have been idle for longer than the maximum idle time limit, avoiding the loss of database connections due to not releasing them. ConclusionThe real-time information exchange platform based on DDS specifications provides an organized data bus for application software systems, making data distribution faster, more efficient, and more reliable; the loose coupling of the real-time information exchange platform makes the development, integration, maintenance, and expansion of application software more convenient at all stages, allowing application software systems to respond more flexibly to changes in demand and functional expansion; the real-time information exchange platform quantifies the transmission mechanisms at all levels into QoS parameters, achieving optimal control of information distribution, thereby better supporting the information transmission needs of various businesses in real-time information systems. The system outlines the technologies and methods for exchanging massive real-time information, elaborating and analyzing the methods of real-time information exchange in IoT and the issues encountered during the exchange process, providing technical ideas for real-time information interaction in IoT from aspects such as real-time reading and analysis of big data files from databases, and log database management.
Due to space constraints, comments are omitted; the complete version can be downloaded and viewed on the Water Table website.
Source: Sanchuan WisdomAuthors: Li Bing, Song ZhifanEditor: Li JingshuaiFirst Review: Zhou QiSecond Review:Zhan Zhijie, Huang Zhenwei
