Internet Of Things Service Platform Research Articles

Group-Based Authentication Methods in The OneM2M Ecosystem

The essential element of the Internet of Things (IoT) environment, the number of devices has traditionally exceeded the number of devices connected to the Internet. This situation is considered positive for the IoT concept but still has negative consequences. Undoubtedly, the most prominent and most important among these results is the security of the devices and the constructed IoT environment. Group-based authentication and authorization methods are crucial to ensure the safety of many IoT devices and the environment. In this study, the “auth” mechanism that performs group-based authentication and authorization processes, serving from the first moment when the devices in the IoT environment are included in the system until they leave the system, has been developed. In the development process of the “auth” mechanism, the Mobius IoT platform, which is evaluated as a golden sample by the oneM2M global organization and developed as an open-source code, is taken as the basis. The “auth” mechanism tested in three different test environments, including simulation, physical, and cloud environments, were tested using five different test scenarios. By using the group management module provided by the IoT service platform and the “auth” mechanism's together, it has been observed that the computational overhead on the devices and the signal traffic in the environment provide up to 4 times efficiency according to performance measurements. With the development of the “auth” mechanism with a flexible structure, it can be operated independently from the IoT server platform, allow-ing interoperability between oneM2M-based IoT server platforms.

Research and Application of the Internet of Things Service Platform Based on Semantic Network

In order to study the Internet of Things service platform based on semantic Network, a service-oriented clustering labeling method is proposed, firstly, a semantic Web service similarity computing method is proposed to solve the shortcomings of the existing methods. This method describes the designed semantic Web service annotation clustering algorithm based on AP algorithm. The distance matrix and related parameters of the algorithm are calculated and assigned according to the results of similarity calculation. The correctness of preference parameter selection will be compared and verified in the service discovery system. The greater the value of damping coefficient, the more iterations, and the slower the convergence rate. However, when the value of damping coefficient is 0.7, the number of iterations is moderate and the convergence rate is the best, which proves that this method has a better effect on service function matching.

Design and Application of Smart City Internet of Things Service Platform Based on Fuzzy Clustering Algorithm

The development of the city is dependent on various information technologies, the core of which is the Internet of Things technology. The traditional multisource information collaboration mode of urban system is relatively single, with low collaboration efficiency and lack of effective measurement of collaboration structure. In this paper, a design scheme of IoT (Internet of Things) service platform for smart cities is proposed, and a multisource information collaborative difference measurement model with a given confidence interval is constructed based on a fuzzy clustering algorithm to meet the needs of developing IoT energy management application services and “smart city” energy management in different environments. In the experiment of participating in the fusion, the number of participating nodes is reduced to about 50 from the third iteration, which is reduced by half. In the traditional algorithm, almost all nodes participate in every fusion process. However, the improved algorithm can greatly reduce the number of participating nodes, thus greatly reducing the computational requirements of the algorithm. The experimental results show that the fuzzy clustering algorithm is effective. The system can be used in vehicle networking, geological disaster prevention, environmental monitoring, and other fields.

Load Balancing Optimization of In-Memory Database for Massive Information Processing of Internet of Things (IoTs)

Based on the analysis of the key technologies of the Internet of Things service platform architecture, a load balancing optimization scheme of in-memory database based on the massive information processing of the Internet of Things service platform is proposed. This scheme firstly proposes a system model that can satisfy the mass sensor information processing under the open platform environment and designs several functional unit modules of the system. By combining these functional units, the service can be configured for thousands of services and tenants. This paper presents an adaptive strategy selection method, which can automatically select the optimization strategy by dividing the position and querying the selection rate to improve the efficiency of the adaptive index algorithm. The index structure is initialized by parallel sorting algorithm, and the query statement is executed and the index structure is optimized by thread level parallel and radix sort methods. An elastic pipeline technique is proposed, which includes an elastic iterator model and a dynamic scheduler. The elastic iterator model is an upgrade of the traditional iterator model, adding the characteristics of dynamic multicore execution. In the process of query processing, dynamic scheduler monitors the load of each node in real time and dynamically adjusts the parallelism, so as to realize the load balance of in-memory database and maximize the utilization of hardware resources. The elastic pipeline realizes the isolation of parallelism from query compilation to avoid inappropriate parallelism allocation caused by missing and insufficient information during query compilation.

Design and application of fog computing and Internet of Things service platform for smart city

Fog computing and Internet of Things technology play a prominent role in the construction of smart cities, which can greatly promote the exchange and management of urban information. Emerging network technologies such as fog computing and the Internet of Things can be used to make it easier to build smart cities, which is conducive to the development of urban business, industry and other industries, as well as tourism and transportation management. Therefore, the realization of a smart city will greatly enhance the comprehensive development strength of the city. We analyze the advantages of fog computing and propose an IoT architecture based on fog computing, which effectively solves the problems of big data processing and network scalability. On this basis, a layered fog computing network architecture is proposed to make the city’s operation more coordinated, efficient and harmonious through various intelligent perceptions, information processing and network transmission means.

A Hadoop Processing Method for Massive Sensor Network Data Based on Internet of Things

Based on the analysis of the architecture of the Internet of Things service platform and the key technologies of cloud computing, a massive sensing information processing scheme based on the Internet of Things service platform is proposed. The scheme first proposes a system architecture model that can satisfy the massive sensor information processing in an open platform environment, and designs multiple functional unit modules of the system. By combining these functional units, service configurability can be realized, facing thousands of services and Tenant. Then, Hadoop open source framework is used to realize the distributed computing of the system, which makes full use of the processing advantages of MapReduce computing model, HBase distributed database and HDFS distributed file system in Hadoop framework, and uses Oracle database as a supplement to realize the system high. Finally, the mass sensor information was deployed and tested. The effectiveness of the Hadoop processing method was verified by analyzing the results of MapReduce parallel computing experiments. The average cache hit rate is 93.1%, which has a high cache hit rate, greatly reduces MySQL database I/O, and improves system performance.

Declarative Construction of Distributed Event-driven IoT Services Based on IoT Resource Models

In Internet of Things (IoT)scenarios, the coordination of physical systems is often complex and rigid. Work to date has not comprehensively explored how to flexibly construct distributed IoT services to satisfy the coordination requirement. In our work, we propose a declarative approach to construct an event-driven IoT service system, where physical devices and systems are explicitly modeled as a service architecture foundation, the service behavior is flexibly declared based on distributed events, and it is step-by-step refined to have rigid service properties while allowing runtime adaptation. As an example, the controllability property of physical systems is discussed. Finally, we establish a distributed event-driven IoT service platform to test our method. Some experiments are performed to concept-prove our work.

A Wireless Internet of Things Architecture Based on Mobile Internet

<p><span style="font-size: small;"><span style="font-family: Times New Roman;">In order to develop a valid wireless Internet of things system, a wireless Internet of things framework based on mobile Internet is designed. The architecture of the Internet of things determines the architecture of the Internet of things business platform. There is no uniform standard for the architecture of the Internet of things service platform. The Internet of things business platform is mostly in an isolated state. The platform uses the common information management platform of Internet websites to manage mobile internet. Combined with the technologies of perception, identification and network transmission in the Internet of things technology, it is a content management Web management information system with both B/S (Browser/Server) and C/S structure (Client/Server). The platform can operate anywhere, and can give full play to the processing capacity of the client PC, and greatly reduce the application server running data load. The experimental results show that compared with the centralized database system, in the same piece of redundant condition, when the test table data is greater than the 1 million and the concurrent number is 100, the distributed database system has shorter concurrent query time and faster system response rate. Based on the above finding, it is concluded that wireless Internet of things technology based on mobile Internet will promote the development of the whole logistics industry and other related industries.</span></span></p>

Internet of Things Online Monitoring System Based on Cloud Computing

<p><span style="font-family: 宋体; font-size: medium;">In order to develop a new convenient online monitoring system for Internet of things, an online monitoring system based on cloud computing is designed. The performance of this new Internet of things technology used in modern agricultural is test by Amazon relational database service (RDS) and ZigBee perception network. By analyzing the Internet of things related technologies and agricultural modernization, the integration framework of the Internet of things, cloud computing and data mining technology in the field of modern agriculture are proposed. Through the modern agricultural Internet of things monitoring system, the Internet of things intelligent gateway, cloud based research and construction of large data analysis and data mining projects are verified. The experimental results show that the relevant parameters of the model are obtained by training about 70% of the original data after adopting the cloud computing. Based on the above finding, it is concluded that the open Internet of things platform needs to be supported by the powerful computing resources. In addition, the cloud computing technology is suitable for the development of the Internet of things service platform.</span></p>

Application and Research for IOT Based on REST Style

The development of sensor networks ,embedded systems and network technique has promoted the blossom of the Internet of things (IOT).However ,most of existing IOT systems are Web Services based and independent development ,which is of high coupling .Besides ,it is quite complex to add new applications to the system. This paper proposes an application of IOT development pattern ,which is based on REST style. It considers the sensor node and data generating process as resource ,and allows isomerous system modules build new application in the way of REST framework. At the same time, we designs the prototype of IOT service platform system and provides the specific implementation technique and system verification.