Investigation on optimization strategy of IoT operation mode based on blockchain

Abstract

Under the call of the national scientific and technological power, the research in the field of sensor technology has made rapid progress. Many smart devices integrating various technical heights have entered the homes of ordinary people. Making these smart devices increasingly intelligent has greatly improved people’s lifestyles and even changed their lives. With the development of blockchain technology and the development of 5G communication equipment and applications, the industrial model of Blockchain and the Internet of Things can also become an important guide for the development of the Internet of Things. Therefore, this paper studies the optimization strategy of the IoT operation mode based on Blockchain. The research results have shown that the IoT operation mode based on Blockchain is superior to the traditional IoT operation mode in terms of node energy consumption, life cycle, and flux performance. Under the IoT operation mode of the Blockchain, the node energy consumption is reduced by about 1.19J on average, and the flux performance is increased by about 21 on average. This showed that the IoT operation model based on Blockchain is feasible.

Keywords

Optimization strategy blockchain Internet of Things technology operation mode

1. Introduction

In the dynamic landscape of the information age and technological advancements, blockchain technology has emerged as a transformative force, finding versatile applications across various fields. Its integration into the Internet of Things (IoT) has particularly captured attention, providing a decentralized and tamper-proof solution that enhances the security and resilience of IoT platforms. Blockchain’s fundamental strength lies in its decentralized nature, offering a distributed ledger resistant to tampering and unauthorized alterations. This characteristic proves advantageous in the IoT realm, where numerous interconnected devices, each assigned a unique identifier, exchange data over networks. Traditional centralized IoT solutions often face vulnerabilities to network attacks and are susceptible to single points of failure [1, 2]. A significant application of blockchain in the IoT domain is the implementation of device shadow services. These services leverage blockchain’s decentralized architecture to establish a distributed and resilient IoT ecosystem. Unlike centralized models prone to disruptions from a single service node failure, decentralized device shadow services ensure that such incidents do not lead to widespread service abnormalities. This robustness is vital for maintaining continuous and secure IoT platform operations.

As the Internet of Things continues to evolve, there is a growing emphasis on the effective application of blockchain, promoting the optimization of the IoT operating model. Research on the operation mode of the Internet of Things [3] based on blockchain has become a top priority, signaling a concerted effort to address current challenges and propel the development of a more secure and resilient IoT ecosystem.

To better promote the research on the optimization strategy of IoT operation mode, this paper studies the impact of IoT operation mode based on Blockchain. First of all, the call of the national scientific and technological forces and the research progress in the field of sensor technology were investigated. It analyzes how smart devices are integrated into ordinary people’s homes, and how these devices improve and change people’s lifestyles. The impact of the development of blockchain technology, 5G communication devices and applications on the Internet of Things industry model is discussed, and how these technologies can become an important guide for the development of the Internet of Things. According to the preliminary research, the core goal of the research is determined to optimize the blockchain-based Internet of Things operation model. Goals were set to compare traditional iot operating models with blockchain-based iot operating models, including key metrics such as node energy consumption, lifecycle and traffic performance. Design the experimental scheme, including building a blockchain-based Internet of Things experimental platform to simulate the actual operation scenario. The collected data is processed and analyzed to calculate the performance of blockchain-based iot operating models in terms of node energy consumption, traffic performance, etc.

Major contributions are as follows:

This new operating model combines the advantages of blockchain technology and IoT sensors, providing new ideas for the development of IoT. Blockchain-based sensor-based IoT operating models show significant advantages in terms of node energy consumption and lifecycle. Blockchain-based IoT operating models also perform well in terms of traffic performance. Through the experimental results and analysis, this paper fully validates the feasibility and advantages of the IoT operating model based on Blockchain. This provides strong support for the development of the Internet of Things field and provides a valuable reference for future research.

Section 2 is related work, Section 3 introduces the basic concept and background information of the method in this paper, Section 3 is the specific implementation details of the method, and Section 5 is the evaluation method

2. Related work

Blockchain technology can solve many problems of IoT, but blockchain itself is not the main design of IoT, which is discussed in many studies. Driven by the large interest in blockchain, the applicability of Siegfried N team’s blockchain technology in IoT applications [4]. The Liang W team believes that IoT privacy remains an object, because of the large size and distributed existence of IoT networks Numerous safety, authentication, and maintenance problems of IoT systems have been overcome by the decentralized existence of blockchain [5]. The Kumar R team’s research paper aims to demonstrate the importance of integrating blockchain technology in IoT environments to ensure trust between IoT devices [6]. Sodhi MMS team users focus on observing the same benefits for the supply chain from any new emerging technology Only subsequence shared experiences can lead to the long “slope of enlightment [7]. The Ahmed I team believes that the significant contributions and rapid developments of advanced artistic intelligence based technologies and approaches, like, machine learning and deep learning, which are applied for extracting accurate information from extensive data, perform a potential role in IoT applications [8]. Li T team constructs a blockchain based privacy pre-service and rewarding private data sharing scheme for IoT to ensure flexible access control of multisharing [9]. Abed S team’s investigation demonstrations that most of lightweight solutions handle either the energy or security issue separately [10]. Analyzed by these studies, the key advantages of blockchain include decentralization, time series data, collective maintenance, and security.

With the rise of IoT big data technology, sensors also play an increasingly important role, so many scholars have also studied this. The Jamshed MA team proposed Sensors are one of the key components of any IoT device. Sensors have a well known historical existence, their integration in wireless technology and the increasing demand for IoT applications have increased their importance and posed challenges in design, integration, and other aspects [11]. For WSN-enabled IoT networks with limited resources, Azbeg K team’s proposes a new routing protocol that combines the advantages of information-centric networks. In order to effectively select the optimal cluster head, a clustering technique based on Black widow optimization is used in this paper [12]. The Sivapalan G team is proposing a lightweight neural network for real-time electrocardiogram (ECG) overall detection and system level power reduction of wearable Internet of Things (IoT) Edge sensors [13]. The Pandya S team proposes an IoT-based sensor-fusion assistive technology for COVID-19 disinfection, which incorporates an automatic sterilizer spray system. This system is equipped with disinfectant sensing units that detect human movement [14]. Pardeshi DKP presents a study that introduces the Fault Detection Framework for healthcare monitoring using IoT Sensors in a wireless environment. Fault detection identifies flaws in a process or system and then isolates the specific fault or issue, as isolating faults provides extra relevant information about the problems [15]. For a resource constrained IoT network, the Hatami M team developed an asymmetric optimal low complexity algorithm – term relax then truncate – and improve that it is optimal as the number of sensors gone to infinity [16]. Under perfect successful interference cancellation coding, Ahmed M team to maximize the total energy efficiency of the IoT network subject to the quality of services of each IoT device [17]. Due to the rise of the Internet of Things, it is necessary to upgrade the level of sensor technology.

3. IoT based on blockchain

(1) Overview of blockchain technology

Blockchain technology, originating as the foundational framework for early Bitcoin, is now gaining widespread recognition and significance worldwide alongside the popularity of Bitcoin [18]. At its core, the blockchain operates through a distributed shared consensus algorithm, processing datasets through smart contracts and automated script code operations. Subsequently, the verified and circulated data is securely collected in a cryptographic form within the blockchain system, benefitting from the protective measures of cryptographic security technology [19]. It’s worth noting that Bitcoin stands as the pioneering example of a blockchain-based cryptocurrency.

If it is abstract from a technical point of view, then blockchain technology can be understood as everyone keeps his or her records in an archive that does not belong to anyone, and the blockchain system is viewed as a state display equipment.

Blockchain technology should be a network concept, but distributed ledger is an accounting concept. The concept of distributed ledger [20] appeared in the 1990s, but at that time, neither computer technology nor artificial intelligence technology could make it possible. It was not until the birth of Bitcoin that the accounting idea of distributed ledgers was truly realized. The distributed ledger is shown in Fig. 1.

Figure 1.

Distributed ledger concept map.

Each blockchain is linked to the parent block itself, the hash string generates the outgoing string, all the way back to the chain of the first block. Because new blocks are created on-chain the consistency of each is ensured by consensus algorithms and handling other synchronizations. A blockchain replication network is a distributed peer-to-peer network where each node stores all transaction data without the need for a third party or second intermediary to manage transactions or data. This distributed data management architecture provides blockchain applications with the benefits of scalability, openness, autonomy, information immutability, and anonymity [21].

The characteristics of blockchain technology are:

Open consensus: Each device is regarded as a node to obtain complete data information.

Decentralization: Each node has an end-to-end relationship, there is no central device or organization, and all nodes jointly maintain the network and have equal status.

De-tripartite: The trust relationship is established directly between nodes without third-party participation.

Concealment: Users are not associated with real identities.

Information cannot be tampered with: In the blockchain system, when block data is tampered with, all subsequent block data and a large number of participating system nodes need to be changed within a certain time of the consensus mechanism to ensure the security of the blockchain.

Traceability: Blockchain uses a blockchain format with time periods to store data to establish the time scale of the data.

Programmability: The blockchain supports the development of application layers on top of scripts, and more complex collaborative operations can be performed through smart contracts.

(2) Blockchain hierarchy

The current blockchain system is often divided into a bottom-up data layer, network layer, consensus layer, contract layer, and application layer. The blockchain has a layered architecture. The following is an explanation of the function of each layer of the architecture:

Data layer: The data layer first includes all relevant information of digital assets, such as data directory, system meeting account information, etc., and uses the blockchain for storage.

Network layer: The network layer includes data sharing mechanisms and data authentication mechanisms with peer-to-peer networks, etc., to maintain synchronization and prevent data authentication between different nodes.

Consensus layer: The blockchain system is essentially an innovation engine. Multiple nodes work at the same time. The results generated by the meeting need to reach a consensus with the nodes of the entire network before they can be aggregated into a chain. Among them, the widely used PoW (Proof of Work) technology requires a lot of time and computing power to try to reach a documented consensus, while the DPoS (Delegated Proof of Stake) process uses all nodes. Voting to choose a way for a large area to receive direct access to the notebook can ensure the correct operation of the blockchain system, which requires a lot of time and computing energy. If it is considered that the data asset management system is a unified chain and highly reliable nodes, then the DPoS consensus algorithm is more concise and efficient, and it is better as a system consensus algorithm.

Contract layer: The contract layer mainly uses smart contracts to automatically write code under the constraints of the control system to perform various functions, such as matching transaction parties.

Application layer: The application layer can provide various external applications of blockchain-based systems, such as conference registration, account management, digital asset verification, distributed transactions, etc.

The hierarchical structure of the blockchain is shown in Fig. 2.

Figure 2.

Blockchain hierarchy.

(3) Application scenarios of blockchain in the Internet of Things

Currently, blockchain technology has applications in many IoT scenarios, including sensors, data storage, identity management, timestamping services, wearable devices, and many other technologies, including agriculture, finance, health, transportation, and various other fields. The specific is shown in Fig. 3.

Figure 3.

Application scenarios of blockchain in the Internet of Things.

The Internet of Things has become one of the most promising technologies and industries in the future. Blockchain technology has the characteristics of encrypted transmission, scalability, and point-to-point structure, which can effectively solve the problems in the Internet of Things. Due to the characteristics of secure password transmission, innovation, and peer-to-peer sharing of blockchain technology, it may become the key to making up for the shortcomings of the Internet of Things. First of all, all data transmitted in the blockchain has been strictly encrypted, and user data and privacy will be relatively safe; and the unified process of the blockchain will also help reduce the chances of malicious entities entering the Internet of Things, providing them with security. In 2016, the Mirai bot affected IoT devices on a large scale in a short period of time. The distributed architecture of the blockchain and the point-to-point characteristics of the subjects can also effectively break the communication barriers between the subjects of the Internet of Things and realize the communication and cooperation between the subjects. Finally, the blockchain acts as a distributed ledger to record the actions of all devices, so it can be used as a general record for a large number of devices in the Internet of Things to record the activity history of the Internet of Things devices, which is more convenient for machine control, maintenance, and repair.

(4) Sensor application and development

Sensors, as information detection and data acquisition [22], can sense the measured physical quantities such as energy, temperature, light, and chemical composition, and translate them into other physical dimensions according to certain laws, usually electrical measurements such as voltage and current, or circuits used to open and close them.

The sensor is generally composed of three parts, and sometimes an auxiliary power supply is required. The sensitive part of the sensor firstly senses the uncharged physical value of the measured object. Then the transducer material converts it into useful electricity and the output electricity of the transducer element generates, modulates, and converts it into a signal that can be displayed and recorded to complete the measurement, conversion, amplification, and transmission of information. The working principle of the sensor is shown in Fig. 4.

Figure 4.

How the sensor works.

Sensors are widely used and have entered many fields of production and human life. They are ubiquitous, affect lives in various ways, and play an important role.

In nuclear power plants, petrochemical plants, automobile manufacturing, steelmaking, cement, glass, and other large-scale manufacturing industries, automatic control is in a very important position. The automatic measurement and control of technological processes such as temperature and discharge water level in the production process are of great significance for the safe, stable, and efficient operation of production equipment, ensuring product quality and production, and saving raw materials and energy. As the main link and important part of the automatic detection of production parameters and automatic control of the production process, sensor performance determines the production efficiency and production capacity of enterprises.

A simple single-loop automatic control system usually consists of a controlled object, a controller, a controller, and a measuring element (sensor). Since the role of the control loop is to work on the content controlled by the participants on the control channel, reducing external interference can control the control parameters to a given value. The function of the sensor here is to provide an information source for the control system, that is, to measure, change, and process the raw production data fed back to the controller. Without accurate and reliable sensors, the production volume cannot be accurately controlled, and the production operation cannot be smooth, safe, efficient, and energy-saving, so sensors are very important [23].

With the rapid development of modern technology, people have put forward more and more requirements for sensors, which also leads to the development of sensors becoming more and more advanced and complex.

4. Application of random distribution network model in blockchain

Therefore, blockchain technology is not one technology, but an aggregate of many technologies that follow a unified concept. This paper will use the random distribution algorithm and consensus idea to optimize the Blockchain.

(1) Poisson point process

In the fields of probability, statistics, and related fields, Poisson point processes are random mathematical objects composed of points randomly located in mathematical space. The Poisson point process is commonly referred to as the Poisson process but is also known as the Poisson random measure, Poisson random point field, or Poisson point field. The most basic research object in random sets is point processes. Generally speaking, a spatial pattern can be described as a set of random points in space, expressed in algorithmic language, it can be expressed as a measurable map $\Phi$ measured from space to point in space $\varpi$ , and the measurable map can be expressed by the discrete sum of Dirichlet measures, which is expressed by the formula as follows:

$\displaystyle\Phi=\sum\limits_{i}{\chi_{a_{i}}}$ (1)

Among them, the random variable $a_{i}$ is a subset of $\varpi$ , and the compact measure of $\Phi$ can be expressed as:

$\displaystyle{A}(Y)=O[{\Phi(Y)}]$ (2)

In the study of spatial processes, the spatial process models are often referred to as Poisson spatial processes. Usually, the fields in the real-world environment are independent of each other, so the Laplace transform of the field process can be defined as follows:

$\displaystyle K_{\Phi}(f)=O\left[\exp\left(-\int_{T}f(a)\Phi(ba)\right.\right]% +\exp\left(-\sum\limits_{i=1}^{a}f\right)$ (3)

$b$ and $a$ are real numbers and $O$ is an imaginary unit. $f$ is a real number that makes the integration path $K_{\Phi}$ within the convergence domain. Among them:

$\displaystyle K_{\Phi}(f)=\exp\left(-\int_{T}(1-o^{-f(a)})ba\right)$ (4)

The previous formula can be used as the Laplace transform of shot noise and signal interference. Two independent and non-interfering Poisson point processes can be superimposed on each other, and the result is still a Poisson point process. If $\beta$ represents the probability density function of the Poisson point process, it can be expressed as:

$\displaystyle{\lambda}^{\prime}(b)=\int\limits_{L}^{m}\lambda(a)\beta(a,b)ya$ (5)

If $\lambda(a)$ it is constant, then:

$\displaystyle\beta(a,{b})=b-a$ (6)

Then for all $b$ , there is:

$\displaystyle{\lambda}^{\prime}(b)=\lambda$ (7)

The Poisson point method is often used to model random and independent network nodes in finite or infinite fields. The total number of base stations in the wireless communication network is predetermined, and the performance of each base station is limited, then a Poisson scoring process is performed. The problem can be solved with a Poisson point process.

(2) Random geometric topology model

Topology is a modern branch of mathematics that studies the phenomenon of continuity, used to study the invariant properties of various spaces under continuous changes. Topology is a branch of geometry, but this type of geometry is different from typical plane geometry and solid geometry. The random geometric topology is a branch of mathematics that studies manifolds and their embeddings. Representative topics include knot theory and braid groups. The stochastic topology model plays an important role in the study of random phenomena. The Boolean model is one of the most famous geometric models and the basis of the continuous laminar flow model. There is a mathematical model formula:

$\displaystyle n=(A_{i}+L_{i})$ (8)

Due to the mutual independence of $A_{i}L_{i}$ and, the Boolean model is characterized by its simplicity of analysis and is often used as the null hypothesis in stochastic geometric models.

The Voronoi model has a wide range of applications in architecture, communication, and other fields. The model also assumes that some communication nodes are randomly distributed in two dimensions, and the space is divided into several areas according to the position of each node. The boundary of the divided area is the midline connecting the boundaries of adjacent areas. According to this division method, each area only belongs to the nearest point, and this division method is more suitable for the actual network communication area. Then the formula can be defined as:

$\displaystyle S_{A}(\phi)=\{{b\in T^{b}\|{b-a}\|+\|{b-a_{i}}\|}\}$ (9)

For the simple point process $\phi=\sum\limits_{i}\delta_{a}$ on the area, the Voronoi model point process is defined as the mark point process as follows:

$\displaystyle w=\sum\limits_{i}\delta({A_{i},S_{A}(\phi)-A_{i}})$ (10)

Voronoi model is the most widely used model in wireless area simulation today, and the area division method of this model conforms to the principle of proximity communication in wireless communication systems.

(3) Random distribution network model

Since the introduction of stochastic network models, they have dominated the research of complex networks. This model suggests that random networks observed in complex systems should be described as purely random. In this way, complexity comes from randomness. The selection and establishment of the network model play a crucial role in the study of system performance. For randomly distributed node $a_{i}$ s, the total received interference power is written as:

$\displaystyle I({a_{i}})=\sum\limits_{B\in 1}{\delta(a_{i}}-B)$ (11)

Because the magnitude of the total interference $I({a_{i}})$ does not depend on the position of the measurement node, the hidden nodes in the space to be measured are not considered. If $\Phi$ it obeys the point process condition, the strength formula is expressed as:

$\displaystyle\lambda(\gamma)=\upsilon s_{b}bt^{b-1}$ (12)

Considering the process of shot noise formation, the IID fading impulse response formula can be obtained:

$\displaystyle g_{t}\tau(t)=g_{t}t^{-x}$ (13)

Then, the Laplace transform formula of interference is as follows:

$\displaystyle K(c)=O[{o}^{\prime}]+\prod\limits_{T\notin 1}{\exp({f(T)})}$ (14)

Since the deletion fading process is independent, the expected value of g can be placed in the inventory, and the calculation formula is expressed as:

$\displaystyle K(c)=\exp(-us_{b}O\{{g_{i}^{m}}\}({1-\delta})$ (15)

To simplify the derivation, a signal frequency in the Gaussian noise region is taken as an example, and the formula is expressed as:

$\displaystyle a(r)=\xi c(r)+m(r)$ (16) $\displaystyle\xi=\sum\limits_{i}{\beta(\|{c_{i}-s}\|})\psi(c_{i})\varpi(c_{i})$ (17)

$\xi$ is the mean, $m$ and a is the variance. Assuming the formula is divided into two parts, there is the calculation formula:

$\displaystyle C_{a}^{x}=C_{NK}^{x}+C_{MK}^{a}$ (18)

The formula is transformed as follows:

$\displaystyle K(f)=\psi\sum\limits_{i=1}^{m}{(r_{n})}$ (19)

$\psi$ is the weighted coefficient, and $K(f)$ is the weighted value. The essence of blockchain technology is to use cryptographic chain protection to verify and store the verification, communication, and trust relationship between data nodes. This is achieved through random distribution network model technology and consensus mechanism. Among them, the data information is maintained by all nodes, and the synchronization of the data information is also accomplished by continuously exchanging information with the adjacent nodes in each node participating in the maintenance.

5. Experiment on optimization strategy of IoT operation mode based on blockchain

(1) Comparison of node energy consumption

In the random distribution network model, the energy consumption of nodes also directly affects the life of the entire device, and the device performance affects the application of the blockchain in the Internet of Things is limited, so how to ensure energy saving and high efficiency of the blockchain is a problem that needs to be solved. This paper analyzes and compares the node energy consumption of the traditional IoT operation mode and the IoT operation mode based on Blockchain, where N is the number of nodes, and the specific data are shown in Table 1.

Table 1
Average node energy consumption comparison chart

Number of nodes/N	Traditional IoT operating model	IoT operation mode based on blockchain
$N=$ 100	1.2	0.25
$N=$ 110	1.5	0.4
$N=$ 120	1.7	0.45
$N=$ 130	1.79	0.51
$N=$ 140	1.82	0.55
$N=$ 150	1.9	0.6
$N=$ 160	2.11	0.65
$N=$ 170	2.35	0.69
$N=$ 180	2.6	0.7

To study the average node energy consumption of the two Internet operation modes more intuitively, this paper plots the survey results in Fig. 5, as shown in Fig. 5.

Figure 5.

Average node energy consumption comparison chart.

It can be seen from Fig. 5 that the node energy consumption of the IoT operation mode based on Blockchain is lower than that of the traditional IoT operation mode. When the number of nodes is 100, the energy consumption of nodes in the traditional IoT operation mode is 0.95J higher than that in the traditional IoT operation mode. When the number of nodes is 110, the energy consumption of the node increases by 1.1J, when the number of nodes is 120, the energy consumption of the node increases by 1.25J, and when the number of nodes is 130, the energy consumption of the node increases by 1.28J. When the number of nodes is 140, the node energy consumption increases by 1.27J, and when the number of nodes is 150, the node energy consumption increases by 1.3J, and the average reduction is about 1.19J. When the number of nodes is 170, the node energy consumption increases by 1.66J, and when the number of nodes is 180, the node energy consumption increases by 1.9J. From the data results, the IoT operation model based on Blockchain can save more energy consumption.

(2) Life cycle comparison

The life cycle can reflect the operating life of IoT devices. This paper analyzes and compares the life cycle of the traditional IoT operation mode and the IoT operation mode based on Blockchain. The experimental results are shown in Fig. 6.

Figure 6.

Average life cycle comparison chart.

It can be seen from Fig. 6 that the life cycle of the IoT operation model based on Blockchain is higher than that of the traditional IoT operation model. This increases the operational longevity of IoT devices. When the number of nodes is 100, the life cycle of the IoT operation model based on Blockchain is up to 350 rounds; when the number of nodes is 110, the life cycle of the IoT operation mode based on Blockchain is up to 320 rounds; when the number of nodes is 120, the life cycle of the IoT operation model based on Blockchain is up to 315 rounds; when the number of nodes is 130, the life cycle of the IoT operation model based on Blockchain is up to 300 rounds; when the number of nodes is 140, the life cycle of the IoT operation model based on Blockchain is up to 316 rounds; when the number of nodes is 150, the life cycle of the IoT operation model based on Blockchain is up to 299 rounds; when the number of nodes is 180, the life cycle of the IoT operation model based on Blockchain is up to 282 rounds, while the life cycle of the traditional IoT operation model is significantly lower than that of the IoT operation model based on Blockchain. To sum up, the IoT operating model based on Blockchain has a longer life cycle.

(3) Comparison of flux performance

The improvement of throughput performance is a hot issue in the current blockchain field. While the traditional IoT operating model can improve the number of transactions per second to some extent, it is not enough. This paper analyzes and compares the throughput performance of the traditional IoT operation mode and the IoT operation mode based on Blockchain, as shown in Fig. 7.

Figure 7.

Comparison of flux performance between two modes.

Figure 8.

Comparison of the recognition of the two modes.

It can be seen from Fig. 7 that the transaction volume per cycle of the IoT operation mode based on Blockchain is significantly higher than the transaction volume under the traditional IoT operation mode. The transaction volume per cycle of the IoT operation mode based on Blockchain is about 39.1, the transaction volume under the traditional IoT operation mode is about 18.1, and the throughput performance is improved by about 21. This shows that the throughput performance of the IoT operation mode based on Blockchain is higher than that of the traditional IoT operation mode.

(4) Satisfaction comparison

To detect how the impact of the IoT operation mode based on Blockchain on the entire IoT was different from the traditional IoT operation mode, a survey was conducted on the satisfaction of relevant technicians under the two operation modes, with a total of 200 respondents. The survey results are four levels of satisfaction, good, fair, and unsatisfactory, as shown in Fig. 8.

According to Fig. 8, the number of satisfied people in the IoT operation model based on Blockchain is 163, and the number of dissatisfied people is only 4; the number of satisfied people with the traditional IoT operation model is 143, and the number of dissatisfied people is 20. The data shows that the IoT operating model based on Blockchain is highly recognized for the entire IoT.

6. Conclusions

Today, with the rapid development of modern technology, the idea of the Internet of Everything is getting closer and closer to reality. With the explosive growth of the number of IoT devices and the continuous improvement of blockchain technology, the combination of IoT and blockchain technology has become a research topic worthy of attention. The IoT operation mode based on Blockchain has become an inevitable trend, so it is of great significance to introduce Blockchain technology in the IoT operation mode. This paper studied the operation mode of the Internet of Things based on Blockchain and compared it from the aspects of node energy consumption, life cycle, throughput, and satisfaction performance. The results showed that the IoT operation mode based on Blockchain was superior to the traditional IoT operation mode. It can be said that opportunities and challenges coexist in this research field, and continuous exploration is needed to allow Blockchain technology to be effectively applied and developed in the field of IoT.

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