Blockchain data privacy protection modeling based on CP-ABE algorithm

The term “cloud of things” is currently in the forefront of computer research topics due to its vital role towards the internet of things. To integrate cloud computing and internet of things into a single technology or worldview, this chapter discussed the evolution of internet of things and cloud computing and reviewed literature on cloud computing and internet of things and their possible integration. The chapter also discussed the importance of cloud internet of things, its architecture, and operation; the need to integrate internet of things and cloud computing; and challenges of cloud internet of things. The chapter then used the identified open issues and future direction to propose a generic cloud internet of things architecture and pilot simulated the results to verify the possibility and effectiveness of cloud computing and internet of things (CIoTs) integration. The researchers believe that the chapter will provide a better insight for anyone who wishes to carry out research in the field of cloud internet of things.

As an important part of the power system, gas insulated switchgear (GIS) will cause serious failures once they break down, threatening the safety of the entire power grid. In the construction of the Ubiquitous Power Internet of Things (UPIoT), the intelligent terminal taking online monitoring as the means keeps the equipment fault samples and forms the sample database, which is of great significance to discover the latent insulation defects of GIS and take necessary measures in advance to ensure the safe and reliable operation of power grid. Aiming at the sample database provided by the intelligent terminal of the Internet of things, this paper proposes a method of GIS partial discharge (PD) using the depth residual network, which effectively improves the accuracy of model recognition. Although the comprehensiveness of the sample has been solved, as a transitional stage, the sample size is relatively small. Therefore, this paper uses transfer learning to solve the problem of high accuracy under the sample. In order to compare the state of art performance of the proposed method, some traditional convolutional networks such as LeNet, AlexNet, and VGG16 are used for comparison. After verification, the recognition accuracy of the deep residual network proposed in this paper is 94.6%, which is significantly higher than other models. At the same time, the parameter amount and storage space of the deep residual network are also significantly lower than those of other networks, further verifying that the model has a broad application space in the UPIoT context.

With the continuous development of new ICT technologies such as big data, cloud computing, internet of things, mobile internet, artificial intelligence, etc. The State Grid Corporation of China (SGCC) will build a full-service ubiquitous power Internet of Things as the “second network” for the integration of power grids. Since March 2018, the ministry of information and communications of SGCC has organized the design work of the full-service ubiquitous power Internet of Things, and using the IMS administrative switching network as the communication support network for the Internet of Things. The construction of IMS administrative switching network faces a series of planning research such as core network, bearer network, access network and so on. The problems of interconnection between headquarters and provincial companies IMS network and public network, and telephone number resource allocation involving number transformation design. Based on the investigation status of State Grid administrative switching network, and the key technologies and architecture of IMS, combined with the characteristics of the electric power network, the transformation number design for IMS administrative switching network was presented. Provide technical guidance for the overall orderly evolution of the company’s switching network and the construction of the Internet of Things.

Demand response (DR) is an effective way to control demand-side resources for power grids through advanced information and communication technologies. In the context of ubiquitous power Internet of Things (UPIoT), single cloud computing can hardly meet the requirements of large-scale real-time data processing in DR. Edge computing is a computing paradigm that deploys computing resources on the edge of the network, and its combination with cloud computing will help improve the ability of the power system to process large-scale sensor data. However, there is currently no comprehensive investigation on the application of edge computing technology in UPIoT DR. In this paper, the concept of DR and recent advances in the context of UPIoT are introduced first. Besides, the concept of edge-cloud computing (ECC) is introduced. Then, a comprehensive review of the existing work on DR based on ECC is presented. Furthermore, according to the existing work of Internet of Things (IoT) architecture based on ECC, a DR edge-cloud collaborative control architecture is proposed to meet the demand of UPIoT for ubiquitous perception and intelligent control. On this basis, the challenges in the practical application of edge computing in the UPIoT DR are introduced.

In the context of the combination of the Internet of Things and the smart grid, how to build a cost-effective ubiquitous Internet of Things needs to solve the shortcomings of cloud computing and big data information interaction in complex network topology, and excessive reliance on manual data annotation. Therefore, it is necessary to incorporate the complex network topology into the ubiquitous Internet of Things construction process. In this paper, through the analysis of the power Internet of Things system structure design, the real-time interaction of data is completed through the access of gateway devices, and a ubiquitous Internet of Things based on Modules/TCP is proposed. The DCS gateway and the security-hardened DSC gateway information transmission mechanism, design a method for real-time interaction between the perception layer and the network layer of a given power network, and provide certain ideas for the construction of the ubiquitous power Internet of Things.

Ubiquitous power Internet of things is an important direction of the development of smart grid, and distribution Internet of things is the application of ubiquitous power Internet of things in the field of distribution. As the terminal unit of state perception, intelligent decision-making and control subject in the distribution Internet of things, intelligent distribution and transformation terminal is the foundation to realize the distribution Internet of things. In order to solve the problems of complex software architecture of traditional distribution and transformation terminal, which is not conducive to expansion, maintenance and transplantation, Microservice + container technology is adopted as the software architecture of intelligent distribution and transformation terminal, which reduces the complexity of development, improves the efficiency of operation and maintenance, and meets the diverse and rapidly changing service requirements of distribution network.

The various services that are offered by IoT and Cloud Service Providers (CSPs) to the customers today feature a pay-per-use service-charging policy. Customers can choose and avail these services when they want, how they want, and from where they want on demand. Demand for these services has increased drastically over the years among individuals and enterprises worldwide, and thus, it is very important to keep up good Quality of Service (QoS). This chapter highlights the history of internet, the gradual evolution of cloud computing, the reasons behind it, evolution and concepts of the Internet of Things (IoT), CloudIoT and its necessities, and various applications and service fields of CloudIoT. This chapter also precisely highlights various concepts regarding maintenance of good QoS, controversies in QoS maintenance, different parameters that the QoS depends on, various problems faced in maintaining those parameters, and the possible solutions for overcoming those problems. Possible directions towards future works are also highlighted in this chapter.

With the comprehensive acceleration of the construction of ubiquitous power Internet of Things by power companies, the construction of power Internet of Things can improve the depth and breadth of information monitoring in all aspects of the power system, monitor and control the operating parameters of important equipment in all aspects, and improve the power system. The monitoring, analysis and prevention capabilities; sensors are the most critical link to the in-depth mastery of information in all aspects of the power of the Internet of Things. As one of the important components of the country, the power company plays a fundamental role in supporting the development of the entire national economy. As power companies continue to develop, they also bring a series of environmental problems. The use of sensor monitoring terminals has become a key issue restricting the development of power Internet of Things. How to build an environment-friendly environment based on environmental protection. The power Internet of Things can improve the safe operation level of the power grid and achieve good economic and social benefits.

This study aims to explore how big data and the Internet of Things can improve the economic benefits of enterprises in online marketing. We first introduced the concept and development trend of big data, Internet of Things, and Internet marketing and then collected a large number of empirical data through the design and implementation of questionnaire survey. Our data analysis results show that the level of use of big data and the Internet of Things has a significant positive impact on business sales. However, there are also some problems and challenges in the implementation of big data and the Internet of Things, such as resource and technology limitations, and legal and ethical issues such as data security and privacy protection. Therefore, we suggest that enterprises should reasonably plan the use of big data and the Internet of Things according to their own resources and capabilities, while constantly upgrading their own technical level, focusing on data security and privacy protection, and tracking the latest technology and market trends. In addition, the government and industry organizations should also formulate and improve relevant policies and standards to support the development of big data and the Internet of Things and protect the interests of consumers. In general, big data and the Internet of Things provide new opportunities and challenges for enterprise online marketing, which need further research and discussion.

In the research of internet of things, considering power allocation of base station from the perspective of energy efficiency (EE) is very meaningful for ubiquitous power internet of things (UPIoT) optimization. In this paper, the EE of UPIoT was analyzed and a new method for internet optimization was proposed by adjusting the small cell transmits power. First, the UPIoT was modeled by two-tier homogeneous Poisson point process (PPP), and the coverage probability of base stations in each tier was derived. Second, according to the definition of EE, and the closed-form of EE was given by deriving the total power consumption and total throughput of UPIoT respectively. At last, the impact of the small cell transmission power on the EE of UPIoT was analyzed, and a small cell power optimization algorithm was proposed to maximize EE. Simulation results show that, the transmission power of cell has a significant impact on the EE of UPIoT. Furthermore, by optimizing the transmission power of small cell, the EE of UPIoT can be improved effectively.

Tasks of Ubiquitous Power Internet of Things run through the power generation, transmission, transformation, distribution, electricity use and other links, requiring advanced communication, artificial intelligence, big data and other technologies. Deep learning chips provide computational power for algorithm execution and data processing, which are indispensable foundations and basic components for intelligent terminals. Therefore, this paper summarizes the challenges and opportunities faced by deep learning chips in the construction of ubiquitous power Internet of Things. Firstly, the four parts of ubiquitous power Internet of Things including terminal layer, network layer, platform layer and application layer are described. Secondly, the key technologies of deep learning technology and deep neural network accelerator involved in deep learning chips are summarized. Finally, the research work of deep learning chips for ubiquitous power Internet of Things is surveyed. The main functions and existing problems are discussed, and the future research work is proposed.

Ubiquitous power Internet of things focuses on data interconnection and information sharing of different devices in communication network, Internet and sensor network. It is an information physical network constructed by combining new technologies such as “big, cloud, thing and mobile”, which has functions of calculation, communication, precise control, remote cooperation and autonomy. The article first expounds the basic concepts and characteristics of the ubiquitous power Internet of Things; secondly, This paper introduces the voltage monitoring method of low-voltage electrical equipment, the method of judgment of the type of power outage event, and the method of identifying the wrong wiring of the watt-hour meter based on high speed power line carrier(HPLC). Then it describes the power wireless private network technology from the aspects of power wireless private network architecture, application scenarios and construction direction under ubiquitous power Internet of things environment. This paper analyzes the ability of communication methods including high speed power line carrier (HPLC) communication and wireless communication to support the data transmission of ubiquitous power Internet of Things.

With the development of ubiquitous power Internet of Things, new types of power services have emerged, and massive data transmission has brought new challenges to power communication networks. Satellite communication is widely used in power and material interconnection business scenarios due to its wide communication coverage and strong communication performance. Firstly, based on the power Internet of Things and its business characteristics and needs, this paper designs a high-low-orbit satellite hybrid networking architecture for power and material-linked services. Then, it studies the overall process of high-low-orbit satellite multi-band switching and uses a layered Bayesian model. The classification perception of multi-scenario power services; finally, the application advantages of multi-band reception technology in the ubiquitous power Internet of Things are summarized. The research indicates that the power Internet of Things involves a wide geographical range and many business scenarios. Applying multi-band fusion receiving technology to the ubiquitous power Internet of Things construction can make up for the shortcomings of the traditional methods, such as emergency services, dispatching services, inspection services, etc. It is of great significance to provide service support to create favorable conditions for the safe and economic operation of the power grid.

The Internet of Things (IoT) connects a plethora of smart devices globally across various applications like smart cities, autonomous vehicles, and health monitoring. Simulation plays a key role in the testing of IoT systems, noting that field testing of a complete IoT product may be infeasible or prohibitively expensive. This paper addresses a specific yet important need in simulation-based testing for IoT: Stress testing of cloud systems that are increasingly employed in IoT applications. Existing stress testing solutions for IoT demand significant computational resources, making them ill-suited and costly. We propose a lean simulation framework designed for IoT cloud stress testing. The framework enables efficient simulation of a large array of IoT and edge devices that communicate with the cloud. To facilitate simulation construction for practitioners, we develop a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">domain-specific language (DSL)</i> , named IoTECS, for generating simulators from model-based specifications. We provide the syntax and semantics of IoTECS and implement IoTECS using Xtext and Xtend. We assess simulators generated from IoTECS specifications for stress testing two real-world systems: a cloud-based IoT monitoring system developed by our industry partner and an IoT-connected vehicle system. Our empirical results indicate that simulators created using IoTECS: (1) achieve best performance when configured with Docker containerization; (2) effectively assess the service capacity of our case-study systems, and (3) outperform industrial stress-testing baseline tools, JMeter and Locust, by a factor of 3.5 in terms of the number of IoT and edge devices they can simulate using identical hardware resources. To gain initial insights about the usefulness of IoTECS in practice, we interviewed two engineers from our industry partner who have firsthand experience with IoTECS. Feedback from these interviews suggests that IoTECS is effective in stress testing IoT cloud systems, saving significant time and effort.

The Internet of Things (IoT) is leading today’s digital transformation. Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare. IoT incorporates various kinds of hardware, communication protocols, and services. This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks. In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers. Likewise, we propose a new classification of security threats and attacks based on new IoT architecture. The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer. First, the physical sensing layer incorporates the basic hardware used by IoT. Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions. Transport protocols are exhibited and the security threats against them are discussed while providing common solutions. Then, the application layer involves application protocols and lightweight encryption algorithms for IoT. Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols. The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond.