The rapid advancement of technology has paved the way for innovative approaches to education.Artificial intelligence(AI),the Internet of Things(IoT),and cloud computing are three transformative technologies reshaping ...The rapid advancement of technology has paved the way for innovative approaches to education.Artificial intelligence(AI),the Internet of Things(IoT),and cloud computing are three transformative technologies reshaping how education is delivered,accessed,and experienced.These technologies enable personalized learning,optimize teaching processes,and make educational resources more accessible to learners worldwide.This paper examines the integration of these technologies into smart education systems,highlighting their applications,benefits,and challenges,and exploring their potential to bridge gaps in educational equity and inclusivity.展开更多
With the rapid development of the Internet of Things(IoT),there are several challenges pertaining to security in IoT applications.Compared with the characteristics of the traditional Internet,the IoT has many problems...With the rapid development of the Internet of Things(IoT),there are several challenges pertaining to security in IoT applications.Compared with the characteristics of the traditional Internet,the IoT has many problems,such as large assets,complex and diverse structures,and lack of computing resources.Traditional network intrusion detection systems cannot meet the security needs of IoT applications.In view of this situation,this study applies cloud computing and machine learning to the intrusion detection system of IoT to improve detection performance.Usually,traditional intrusion detection algorithms require considerable time for training,and these intrusion detection algorithms are not suitable for cloud computing due to the limited computing power and storage capacity of cloud nodes;therefore,it is necessary to study intrusion detection algorithms with low weights,short training time,and high detection accuracy for deployment and application on cloud nodes.An appropriate classification algorithm is a primary factor for deploying cloud computing intrusion prevention systems and a prerequisite for the system to respond to intrusion and reduce intrusion threats.This paper discusses the problems related to IoT intrusion prevention in cloud computing environments.Based on the analysis of cloud computing security threats,this study extensively explores IoT intrusion detection,cloud node monitoring,and intrusion response in cloud computing environments by using cloud computing,an improved extreme learning machine,and other methods.We use the Multi-Feature Extraction Extreme Learning Machine(MFE-ELM)algorithm for cloud computing,which adds a multi-feature extraction process to cloud servers,and use the deployed MFE-ELM algorithm on cloud nodes to detect and discover network intrusions to cloud nodes.In our simulation experiments,a classical dataset for intrusion detection is selected as a test,and test steps such as data preprocessing,feature engineering,model training,and result analysis are performed.The experimental results show that the proposed algorithm can effectively detect and identify most network data packets with good model performance and achieve efficient intrusion detection for heterogeneous data of the IoT from cloud nodes.Furthermore,it can enable the cloud server to discover nodes with serious security threats in the cloud cluster in real time,so that further security protection measures can be taken to obtain the optimal intrusion response strategy for the cloud cluster.展开更多
The world is rapidly changing with the advance of information technology.The expansion of the Internet of Things(IoT)is a huge step in the development of the smart city.The IoT consists of connected devices that trans...The world is rapidly changing with the advance of information technology.The expansion of the Internet of Things(IoT)is a huge step in the development of the smart city.The IoT consists of connected devices that transfer information.The IoT architecture permits on-demand services to a public pool of resources.Cloud computing plays a vital role in developing IoT-enabled smart applications.The integration of cloud computing enhances the offering of distributed resources in the smart city.Improper management of security requirements of cloud-assisted IoT systems can bring about risks to availability,security,performance,condentiality,and privacy.The key reason for cloud-and IoT-enabled smart city application failure is improper security practices at the early stages of development.This article proposes a framework to collect security requirements during the initial development phase of cloud-assisted IoT-enabled smart city applications.Its three-layered architecture includes privacy preserved stakeholder analysis(PPSA),security requirement modeling and validation(SRMV),and secure cloud-assistance(SCA).A case study highlights the applicability and effectiveness of the proposed framework.A hybrid survey enables the identication and evaluation of signicant challenges.展开更多
Due to its decentralized,tamper-proof,and trust-free characteristics,blockchain is used in the Internet of Things(IoT)to guarantee the reliability of data.However,some technical flaws in blockchain itself prevent the ...Due to its decentralized,tamper-proof,and trust-free characteristics,blockchain is used in the Internet of Things(IoT)to guarantee the reliability of data.However,some technical flaws in blockchain itself prevent the development of these applications,such as the issue with linearly growing storage capacity of blockchain systems.On the other hand,there is a lack of storage resources for sensor devices in IoT,and numerous sensor devices will generate massive data at ultra-high speed,which makes the storage problem of the IoT enabled by blockchain more prominent.There are various solutions to reduce the storage burden by modifying the blockchain’s storage policy,but most of them do not consider the willingness of peers.In attempt to make the blockchain more compatible with the IoT,this paper proposes a storage optimization scheme that revisits the system data storage problem from amore practically oriented standpoint.Peers will only store transactional data that they are directly involved in.In addition,a transaction verification model is developed to enable peers to undertake transaction verification with the aid of cloud computing,and an incentive mechanism is premised on the storage optimization scheme to assure data integrity.The results of the simulation experiments demonstrate the proposed scheme’s advantage in terms of storage and throughput.展开更多
Smart appliances and renewable energy resources are becoming an integral part of smart homes. Nowadays, home appliances are communicating with each other with home short-range home area gateways, using existing netwo...Smart appliances and renewable energy resources are becoming an integral part of smart homes. Nowadays, home appliances are communicating with each other with home short-range home area gateways, using existing network communication protocols such as ZigBee, Bluetooth, RFID, and WiFi. A Gateway allows homeowners and utilities to communicate remotely with the appliances via long-range communication networks such as GPRS, WiMax, LTE, and power liner carrier. This paper utilizes the Internet of Things （IoT） concepts to monitor and control home appliances. Moreover, this paper proposes a framework that enables the integration and the coordination of Human-to-Appliance, Utility-to- Appliance, and Appliance-to-Appliance. Utilizing the concepts of Internet of Things leads to one standard communication protocols, TCP/IPV6, which overcomes the many diverse home area networks and neighborhood area networks protocols. This work proposes a cloud based framework that enables the IoTs integration and supports the coordination between devices, as well as with device-human interaction. A prototype is designed, implemented, and tested to validate the proposed solution.展开更多
Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply cha...Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply chain management. Cloud-Based Manufacturing is a recent on-demand model of manufacturing that is leveraging IoT technologies. While Cloud-Based Manufacturing enables on-demand access to manufacturing resources, a trusted intermediary is required for transactions between the users who wish to avail manufacturing services. We present a decentralized, peer-to-peer platform called BPIIoT for Industrial Internet of Things based on the Block chain technology. With the use of Blockchain technology, the BPIIoT platform enables peers in a decentralized, trustless, peer-to-peer network to interact with each other without the need for a trusted intermediary.展开更多
In recent years,the Internet of Things technology has developed rapidly,and smart Internet of Things devices have also been widely popularized.A large amount of data is generated every moment.Now we are in the era of ...In recent years,the Internet of Things technology has developed rapidly,and smart Internet of Things devices have also been widely popularized.A large amount of data is generated every moment.Now we are in the era of big data in the Internet of Things.The rapid growth of massive data has brought great challenges to storage technology,which cannot be well coped with by traditional storage technology.The demand for massive data storage has given birth to cloud storage technology.Load balancing technology plays an important role in improving the performance and resource utilization of cloud storage systems.Therefore,it is of great practical significance to study how to improve the performance and resource utilization of cloud storage systems through load balancing technology.On the basis of studying the read strategy of Swift,this article proposes a reread strategy based on load balancing of storage resources to solve the problem of unbalanced read load between interruptions caused by random data copying in Swift.The storage asynchronously tracks the I/O conversion to select the storage with the smallest load for asynchronous reading.The experimental results indicate that the proposed strategy can achieve a better load balancing state in terms of storage I/O utilization and CPU utilization than the random read strategy index of Swift.展开更多
In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to im...In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.展开更多
The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machin...The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machine learning models,deep learning models have gained more attention from the research community,as they have shown better results with a large volume of data compared to shallow learning.However,no comprehensive survey has been conducted on integrated IoT-and computing-based systems that deploy deep learning for disease detection.This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection,using the most recent papers on IoT-based disease detection systems that include computing approaches,such as cloud,edge,and fog.Their analysis focused on an IoT deep learning architecture suitable for disease detection.It also recognizes the different factors that require the attention of researchers to develop better IoT disease detection systems.This study can be helpful to researchers interested in developing better IoT-based disease detection and prediction systems based on deep learning using hybrid algorithms.展开更多
Technological advances in recent years have significantly changed the way an operating room works.This work aims to create a platformto solve the problems of operating room occupancy and prepare the rooms with an envi...Technological advances in recent years have significantly changed the way an operating room works.This work aims to create a platformto solve the problems of operating room occupancy and prepare the rooms with an environment that is favorable for all operations.Using this system,a doctor can control all operation rooms,especially before an operation,and monitor their temperature and humidity to prepare for the operation.Also,in the event of a problem,an alert is sent to the nurse responsible for the room and medical stuff so that the problem can be resolved.The platformis tested using a Raspberry PI card and sensors.The sensors are connected to a cloud layer that collects and analyzes the temperature and humidity values obtained from the environment during an operation.The result of experimentations is visualized through a web application and an Android application.The platform also considers the security aspects such as authorization to access application functionalities for the Web and the mobile applications.We can also test and evaluate the system’s existing problems and vulnerabilities using the IEEE and owasp IoT standards.Finally,the proposed framework is extended with a model based testing technique that may be adopted for validating the security aspects.展开更多
Nowadays,Multi Robotic System(MRS)consisting of different robot shapes,sizes and capabilities has received significant attention from researchers and are being deployed in a variety of real-world applications.From sen...Nowadays,Multi Robotic System(MRS)consisting of different robot shapes,sizes and capabilities has received significant attention from researchers and are being deployed in a variety of real-world applications.From sensors and actuators improved by communication technologies to powerful computing systems utilizing advanced Artificial Intelligence(AI)algorithms have rapidly driven the development of MRS,so the Internet of Things(IoT)in MRS has become a new topic,namely the Internet of Robotic Things(IoRT).This paper summarizes a comprehensive survey of state-of-the-art technologies for mobile robots,including general architecture,benefits,challenges,practical applications,and future research directions.In addition,remarkable research of i)multirobot navigation,ii)network architecture,routing protocols and communications,and iii)coordination among robots as well as data analysis via external computing(cloud,fog,edge,edge-cloud)are merged with the IoRT architecture according to their applicability.Moreover,security is a long-term challenge for IoRT because of various attack vectors,security flaws,and vulnerabilities.Security threats,attacks,and existing solutions based on IoRT architectures are also under scrutiny.Moreover,the identification of environmental situations that are crucial for all types of IoRT applications,such as the detection of objects,human,and obstacles,is also critically reviewed.Finally,future research directions are given by analyzing the challenges of IoRT in mobile robots.展开更多
The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it...The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it is difficult to predict the congestion state of the link-end accurately at the source.In this paper,we presented an improved NUMFabric algorithm for calculating the overall congestion price.In the proposed scheme,the whole network structure had been obtained by the central control server in the Software Defined Network,and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.In this scheme,the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information.Based on the historical data,the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm.The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm.We evaluate this evolved NUMFabric algorithm in NS3,which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.展开更多
With the improvement of the degree of aging,the traditional pension model can no longer meet the growing needs of the elderly.Therefore,it is necessary to use the intelligent means of information technology to improve...With the improvement of the degree of aging,the traditional pension model can no longer meet the growing needs of the elderly.Therefore,it is necessary to use the intelligent means of information technology to improve the level of pension services.This paper will integrate multi-sensor fusion technology,NB-IoT communication technology and cloud platform technology to develop and design a smart pension online monitoring system to realize real-time collection of human health and motion status information and realize monitoring platform management.In this system,STM32 microcontroller will be used as the main control module,and MAX30102,ADXL345 and DS18B20 sensors will be used to collect the heart rate,blood oxygen,displacement and body temperature of the human body in real time.On the one hand,the communication part is completed by the BC20 Internet of Things module.The data transmission between the terminal detection device and the cloud platform,on the other hand,the HC-42 Bluetooth module is used to complete the data communication with the mobile phone.The test results show that the system can collect and process data accurately in real time and maintain good communication with the cloud platform and mobile phone.The designed system has strong pertinence,easy operation,high reliability and broad development prospects.展开更多
The concept of Internet of Everything is like a revolutionary storm,bringing the whole society closer together.Internet of Things(IoT)has played a vital role in the process.With the rise of the concept of Industry 4.0...The concept of Internet of Everything is like a revolutionary storm,bringing the whole society closer together.Internet of Things(IoT)has played a vital role in the process.With the rise of the concept of Industry 4.0,intelligent transformation is taking place in the industrial field.As a new concept,an industrial IoT system has also attracted the attention of industry and academia.In an actual industrial scenario,a large number of devices will generate numerous industrial datasets.The computing efficiency of an industrial IoT system is greatly improved with the help of using either cloud computing or edge computing.However,privacy issues may seriously harmed interests of users.In this article,we summarize privacy issues in a cloud-or an edge-based industrial IoT system.The privacy analysis includes data privacy,location privacy,query and identity privacy.In addition,we also review privacy solutions when applying software defined network and blockchain under the above two systems.Next,we analyze the computational complexity and privacy protection performance of these solutions.Finally,we discuss open issues to facilitate further studies.展开更多
Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural se...Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural services,cultural resources,and cultural platforms,bringing individuals with richer humanistic experience,increasing economic benefits for the cultural sector,and promoting the development of cultural heritage protection and education.At present,IoCT has received widespread attention in both industry and academia.To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications,this survey provides a comprehensive overview of the IoCT components and key technologies.A comparison study of representative IoCT systems is presented according to their applicability.A general platform architecture of IoCT is proposed to link cultural objects with the internet and human.Finally,open issues for research challenges and future opportunities of IoCT are also studied in this paper.展开更多
Given the recent developments of Internet of Things (IoT) researchers and academics are trying to utilize this concept for different innovative applications. One of those applications of IoT is the remote laboratories...Given the recent developments of Internet of Things (IoT) researchers and academics are trying to utilize this concept for different innovative applications. One of those applications of IoT is the remote laboratories, where real hardware/software experimentation systems can be controlled and manipulated over the web. During the COVID-19 pandemic, this has become almost essential for academic and research activities. The paper starts with highlighting the necessity and current status of remote laboratories in terms of shortcomings and possible recourse. With these in mind, the second part illustrates an infrastructure of a remote laboratory facility as well as describes the development of a number of prototype remote laboratories that are utilized for academic activities.展开更多
The development of the Internet of Things(IoT)has rapidly progressed,revolutionizing numerous industries and transforming how we interact with technology.IoT relies on seamless connectivity between devices,allowing th...The development of the Internet of Things(IoT)has rapidly progressed,revolutionizing numerous industries and transforming how we interact with technology.IoT relies on seamless connectivity between devices,allowing them to collect,share,and analyze data.As a result,compatibility and connectivity have become major concerns for customers adopting smart devices.Achieving compatibility in a smart device is a shared responsibility between the IoT platform provider and the smart device manufacturer.However,the impact of their respective efforts on smart device compatibility depends on investment efficiency and the service level.In this study,we develop a game-theoretical model to examine how investment efficiency affects the incentives of the upstream platform and the downstream manufacturer to exert compatibility efforts under the licensing pricing and revenue sharing models in a supply chain setting.Our findings indicate that,given a certain IoT platform service level,a manufacturer’s effort decreases as the relative weight decreases in the licensing pricing model.Additionally,when the platform’s effort cost is lower,the platform can invest more in compatibility,thereby improving the compatibility of smart devices.In such cases,the manufacturer can benefit from the platform’s incentives to exert compatibility efforts by reducing her efforts.We also identify two effects:the compatibility effect and the service value-added effect.When the relative weight of compatibility is small,the role of platform compatibility diminishes.Consequently,the platform cannot increase technology licensing fees to augment IoT service income,reducing profits.Our results also provide insights into how an IoT platform provider can strategically target a particular IoT service based on their cost characteristics and service level in smart device supply chains.展开更多
The Internet of Things(IoT)provides new opportunities for different IoT platforms connecting various devices together.The need to identify those devices is the foremost important to perform any kind of operation.Many ...The Internet of Things(IoT)provides new opportunities for different IoT platforms connecting various devices together.The need to identify those devices is the foremost important to perform any kind of operation.Many organizations and standard bodies that provide specifications and frameworks for the IoT currently have their own identification mechanisms.Some existing industrial identification mechanisms can also be used in the IoT.There is no common Identification Scheme(IS)for the IoT as yet,because of the political and commercial differences amongst the standard bodies.The unavailability of a unified IS method makes the inter-working among IoT platforms challenging.This paper analyses and compares ISs used by several selected IoT platforms.This work will help in understanding the need for a common identification mechanism to provide inter-working among different IoT platforms.展开更多
The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after a...The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.展开更多
Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespre...Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.展开更多
文摘The rapid advancement of technology has paved the way for innovative approaches to education.Artificial intelligence(AI),the Internet of Things(IoT),and cloud computing are three transformative technologies reshaping how education is delivered,accessed,and experienced.These technologies enable personalized learning,optimize teaching processes,and make educational resources more accessible to learners worldwide.This paper examines the integration of these technologies into smart education systems,highlighting their applications,benefits,and challenges,and exploring their potential to bridge gaps in educational equity and inclusivity.
基金funded by the Key Research and Development plan of Jiangsu Province (Social Development)No.BE20217162Jiangsu Modern Agricultural Machinery Equipment and Technology Demonstration and Promotion Project No.NJ2021-19.
文摘With the rapid development of the Internet of Things(IoT),there are several challenges pertaining to security in IoT applications.Compared with the characteristics of the traditional Internet,the IoT has many problems,such as large assets,complex and diverse structures,and lack of computing resources.Traditional network intrusion detection systems cannot meet the security needs of IoT applications.In view of this situation,this study applies cloud computing and machine learning to the intrusion detection system of IoT to improve detection performance.Usually,traditional intrusion detection algorithms require considerable time for training,and these intrusion detection algorithms are not suitable for cloud computing due to the limited computing power and storage capacity of cloud nodes;therefore,it is necessary to study intrusion detection algorithms with low weights,short training time,and high detection accuracy for deployment and application on cloud nodes.An appropriate classification algorithm is a primary factor for deploying cloud computing intrusion prevention systems and a prerequisite for the system to respond to intrusion and reduce intrusion threats.This paper discusses the problems related to IoT intrusion prevention in cloud computing environments.Based on the analysis of cloud computing security threats,this study extensively explores IoT intrusion detection,cloud node monitoring,and intrusion response in cloud computing environments by using cloud computing,an improved extreme learning machine,and other methods.We use the Multi-Feature Extraction Extreme Learning Machine(MFE-ELM)algorithm for cloud computing,which adds a multi-feature extraction process to cloud servers,and use the deployed MFE-ELM algorithm on cloud nodes to detect and discover network intrusions to cloud nodes.In our simulation experiments,a classical dataset for intrusion detection is selected as a test,and test steps such as data preprocessing,feature engineering,model training,and result analysis are performed.The experimental results show that the proposed algorithm can effectively detect and identify most network data packets with good model performance and achieve efficient intrusion detection for heterogeneous data of the IoT from cloud nodes.Furthermore,it can enable the cloud server to discover nodes with serious security threats in the cloud cluster in real time,so that further security protection measures can be taken to obtain the optimal intrusion response strategy for the cloud cluster.
基金Taif University Researchers Supporting Project No.(TURSP-2020/126),Taif University,Taif,Saudi Arabia。
文摘The world is rapidly changing with the advance of information technology.The expansion of the Internet of Things(IoT)is a huge step in the development of the smart city.The IoT consists of connected devices that transfer information.The IoT architecture permits on-demand services to a public pool of resources.Cloud computing plays a vital role in developing IoT-enabled smart applications.The integration of cloud computing enhances the offering of distributed resources in the smart city.Improper management of security requirements of cloud-assisted IoT systems can bring about risks to availability,security,performance,condentiality,and privacy.The key reason for cloud-and IoT-enabled smart city application failure is improper security practices at the early stages of development.This article proposes a framework to collect security requirements during the initial development phase of cloud-assisted IoT-enabled smart city applications.Its three-layered architecture includes privacy preserved stakeholder analysis(PPSA),security requirement modeling and validation(SRMV),and secure cloud-assistance(SCA).A case study highlights the applicability and effectiveness of the proposed framework.A hybrid survey enables the identication and evaluation of signicant challenges.
基金We would also thank the support from the National Natural Science Foundation of China(Nos.62172182,62202118,61962009)the Top Technology Talent Project from Guizhou Education Department(Qian jiao ji[2022]073)The Opening Foundation of Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province(Grant No.ZNKZN2021-07).
文摘Due to its decentralized,tamper-proof,and trust-free characteristics,blockchain is used in the Internet of Things(IoT)to guarantee the reliability of data.However,some technical flaws in blockchain itself prevent the development of these applications,such as the issue with linearly growing storage capacity of blockchain systems.On the other hand,there is a lack of storage resources for sensor devices in IoT,and numerous sensor devices will generate massive data at ultra-high speed,which makes the storage problem of the IoT enabled by blockchain more prominent.There are various solutions to reduce the storage burden by modifying the blockchain’s storage policy,but most of them do not consider the willingness of peers.In attempt to make the blockchain more compatible with the IoT,this paper proposes a storage optimization scheme that revisits the system data storage problem from amore practically oriented standpoint.Peers will only store transactional data that they are directly involved in.In addition,a transaction verification model is developed to enable peers to undertake transaction verification with the aid of cloud computing,and an incentive mechanism is premised on the storage optimization scheme to assure data integrity.The results of the simulation experiments demonstrate the proposed scheme’s advantage in terms of storage and throughput.
基金supported in part by the Department of Computer Science and Engineering at the American University of Sharjah,UAE
文摘Smart appliances and renewable energy resources are becoming an integral part of smart homes. Nowadays, home appliances are communicating with each other with home short-range home area gateways, using existing network communication protocols such as ZigBee, Bluetooth, RFID, and WiFi. A Gateway allows homeowners and utilities to communicate remotely with the appliances via long-range communication networks such as GPRS, WiMax, LTE, and power liner carrier. This paper utilizes the Internet of Things （IoT） concepts to monitor and control home appliances. Moreover, this paper proposes a framework that enables the integration and the coordination of Human-to-Appliance, Utility-to- Appliance, and Appliance-to-Appliance. Utilizing the concepts of Internet of Things leads to one standard communication protocols, TCP/IPV6, which overcomes the many diverse home area networks and neighborhood area networks protocols. This work proposes a cloud based framework that enables the IoTs integration and supports the coordination between devices, as well as with device-human interaction. A prototype is designed, implemented, and tested to validate the proposed solution.
文摘Internet of Things (IoT) are being adopted for industrial and manufacturing applications such as manufacturing automation, remote machine diagnostics, prognostic health management of industrial machines and supply chain management. Cloud-Based Manufacturing is a recent on-demand model of manufacturing that is leveraging IoT technologies. While Cloud-Based Manufacturing enables on-demand access to manufacturing resources, a trusted intermediary is required for transactions between the users who wish to avail manufacturing services. We present a decentralized, peer-to-peer platform called BPIIoT for Industrial Internet of Things based on the Block chain technology. With the use of Blockchain technology, the BPIIoT platform enables peers in a decentralized, trustless, peer-to-peer network to interact with each other without the need for a trusted intermediary.
基金This work is supported by the Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.201714)Weihai Science and Technology Development Program(2016DXGJMS15)+1 种基金Key Research and Development Program in Shandong Provincial(2017GGX90103)Weihai Scientific Research and Innovation Fund(2020).
文摘In recent years,the Internet of Things technology has developed rapidly,and smart Internet of Things devices have also been widely popularized.A large amount of data is generated every moment.Now we are in the era of big data in the Internet of Things.The rapid growth of massive data has brought great challenges to storage technology,which cannot be well coped with by traditional storage technology.The demand for massive data storage has given birth to cloud storage technology.Load balancing technology plays an important role in improving the performance and resource utilization of cloud storage systems.Therefore,it is of great practical significance to study how to improve the performance and resource utilization of cloud storage systems through load balancing technology.On the basis of studying the read strategy of Swift,this article proposes a reread strategy based on load balancing of storage resources to solve the problem of unbalanced read load between interruptions caused by random data copying in Swift.The storage asynchronously tracks the I/O conversion to select the storage with the smallest load for asynchronous reading.The experimental results indicate that the proposed strategy can achieve a better load balancing state in terms of storage I/O utilization and CPU utilization than the random read strategy index of Swift.
基金supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIT) (No.2021R1C1C1013133)supported by the Institute of Information and Communications Technology Planning and Evaluation (IITP)grant funded by the Korea Government (MSIT) (RS-2022-00167197,Development of Intelligent 5G/6G Infrastructure Technology for The Smart City)supported by the Soonchunhyang University Research Fund.
文摘In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.
文摘The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machine learning models,deep learning models have gained more attention from the research community,as they have shown better results with a large volume of data compared to shallow learning.However,no comprehensive survey has been conducted on integrated IoT-and computing-based systems that deploy deep learning for disease detection.This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection,using the most recent papers on IoT-based disease detection systems that include computing approaches,such as cloud,edge,and fog.Their analysis focused on an IoT deep learning architecture suitable for disease detection.It also recognizes the different factors that require the attention of researchers to develop better IoT disease detection systems.This study can be helpful to researchers interested in developing better IoT-based disease detection and prediction systems based on deep learning using hybrid algorithms.
基金Taif University Researchers Supporting Project(TURSP-2020/36),Taif University,Taif,Saudi Arabia.
文摘Technological advances in recent years have significantly changed the way an operating room works.This work aims to create a platformto solve the problems of operating room occupancy and prepare the rooms with an environment that is favorable for all operations.Using this system,a doctor can control all operation rooms,especially before an operation,and monitor their temperature and humidity to prepare for the operation.Also,in the event of a problem,an alert is sent to the nurse responsible for the room and medical stuff so that the problem can be resolved.The platformis tested using a Raspberry PI card and sensors.The sensors are connected to a cloud layer that collects and analyzes the temperature and humidity values obtained from the environment during an operation.The result of experimentations is visualized through a web application and an Android application.The platform also considers the security aspects such as authorization to access application functionalities for the Web and the mobile applications.We can also test and evaluate the system’s existing problems and vulnerabilities using the IEEE and owasp IoT standards.Finally,the proposed framework is extended with a model based testing technique that may be adopted for validating the security aspects.
基金This research was supported by the Ministry of Higher Education,Malaysia(MoHE)through Fundamental Research Grant Scheme(FRGS/1/2021/TK0/UTAR/02/9)The work was also supported by the Universiti Tunku Abdul Rahman(UTAR),Malaysia,under UTAR Research Fund(UTARRF)(IPSR/RMC/UTARRF/2021C1/T05).
文摘Nowadays,Multi Robotic System(MRS)consisting of different robot shapes,sizes and capabilities has received significant attention from researchers and are being deployed in a variety of real-world applications.From sensors and actuators improved by communication technologies to powerful computing systems utilizing advanced Artificial Intelligence(AI)algorithms have rapidly driven the development of MRS,so the Internet of Things(IoT)in MRS has become a new topic,namely the Internet of Robotic Things(IoRT).This paper summarizes a comprehensive survey of state-of-the-art technologies for mobile robots,including general architecture,benefits,challenges,practical applications,and future research directions.In addition,remarkable research of i)multirobot navigation,ii)network architecture,routing protocols and communications,and iii)coordination among robots as well as data analysis via external computing(cloud,fog,edge,edge-cloud)are merged with the IoRT architecture according to their applicability.Moreover,security is a long-term challenge for IoRT because of various attack vectors,security flaws,and vulnerabilities.Security threats,attacks,and existing solutions based on IoRT architectures are also under scrutiny.Moreover,the identification of environmental situations that are crucial for all types of IoRT applications,such as the detection of objects,human,and obstacles,is also critically reviewed.Finally,future research directions are given by analyzing the challenges of IoRT in mobile robots.
基金supported by National Key R&D Program of China—Industrial Internet Application Demonstration-Sub-topic Intelligent Network Operation and Security Protection(2018YFB1802400).
文摘The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it is difficult to predict the congestion state of the link-end accurately at the source.In this paper,we presented an improved NUMFabric algorithm for calculating the overall congestion price.In the proposed scheme,the whole network structure had been obtained by the central control server in the Software Defined Network,and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.In this scheme,the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information.Based on the historical data,the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm.The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm.We evaluate this evolved NUMFabric algorithm in NS3,which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.
基金supported by Jiangsu Provincial Natural Science Fund(BK20150247)the Fundamental Research Funds for Postgraduate Research&Practice Innovation Program of Jiangsu Province(XSJCX22_36,XSJCX22_44,SJCX22_1479)
文摘With the improvement of the degree of aging,the traditional pension model can no longer meet the growing needs of the elderly.Therefore,it is necessary to use the intelligent means of information technology to improve the level of pension services.This paper will integrate multi-sensor fusion technology,NB-IoT communication technology and cloud platform technology to develop and design a smart pension online monitoring system to realize real-time collection of human health and motion status information and realize monitoring platform management.In this system,STM32 microcontroller will be used as the main control module,and MAX30102,ADXL345 and DS18B20 sensors will be used to collect the heart rate,blood oxygen,displacement and body temperature of the human body in real time.On the one hand,the communication part is completed by the BC20 Internet of Things module.The data transmission between the terminal detection device and the cloud platform,on the other hand,the HC-42 Bluetooth module is used to complete the data communication with the mobile phone.The test results show that the system can collect and process data accurately in real time and maintain good communication with the cloud platform and mobile phone.The designed system has strong pertinence,easy operation,high reliability and broad development prospects.
基金the National Natural Science Foundation of China(Grant No.61871023 and 61931001)Beijing Natural Science Foundation(Grant No.4202054).
文摘The concept of Internet of Everything is like a revolutionary storm,bringing the whole society closer together.Internet of Things(IoT)has played a vital role in the process.With the rise of the concept of Industry 4.0,intelligent transformation is taking place in the industrial field.As a new concept,an industrial IoT system has also attracted the attention of industry and academia.In an actual industrial scenario,a large number of devices will generate numerous industrial datasets.The computing efficiency of an industrial IoT system is greatly improved with the help of using either cloud computing or edge computing.However,privacy issues may seriously harmed interests of users.In this article,we summarize privacy issues in a cloud-or an edge-based industrial IoT system.The privacy analysis includes data privacy,location privacy,query and identity privacy.In addition,we also review privacy solutions when applying software defined network and blockchain under the above two systems.Next,we analyze the computational complexity and privacy protection performance of these solutions.Finally,we discuss open issues to facilitate further studies.
基金supported by National Natural Science Foundation of China(62172155)The National Key Research and Development Program of China(2019YFB1405702)。
文摘Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural services,cultural resources,and cultural platforms,bringing individuals with richer humanistic experience,increasing economic benefits for the cultural sector,and promoting the development of cultural heritage protection and education.At present,IoCT has received widespread attention in both industry and academia.To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications,this survey provides a comprehensive overview of the IoCT components and key technologies.A comparison study of representative IoCT systems is presented according to their applicability.A general platform architecture of IoCT is proposed to link cultural objects with the internet and human.Finally,open issues for research challenges and future opportunities of IoCT are also studied in this paper.
文摘Given the recent developments of Internet of Things (IoT) researchers and academics are trying to utilize this concept for different innovative applications. One of those applications of IoT is the remote laboratories, where real hardware/software experimentation systems can be controlled and manipulated over the web. During the COVID-19 pandemic, this has become almost essential for academic and research activities. The paper starts with highlighting the necessity and current status of remote laboratories in terms of shortcomings and possible recourse. With these in mind, the second part illustrates an infrastructure of a remote laboratory facility as well as describes the development of a number of prototype remote laboratories that are utilized for academic activities.
基金supported in part by International Chinese Language Education Research Foundation of Ministry of Education of China,under Grant No.23YH39DPhilosophical and Social Science Planning Project of Tianjin,under grants No.TJGLQN23-006。
文摘The development of the Internet of Things(IoT)has rapidly progressed,revolutionizing numerous industries and transforming how we interact with technology.IoT relies on seamless connectivity between devices,allowing them to collect,share,and analyze data.As a result,compatibility and connectivity have become major concerns for customers adopting smart devices.Achieving compatibility in a smart device is a shared responsibility between the IoT platform provider and the smart device manufacturer.However,the impact of their respective efforts on smart device compatibility depends on investment efficiency and the service level.In this study,we develop a game-theoretical model to examine how investment efficiency affects the incentives of the upstream platform and the downstream manufacturer to exert compatibility efforts under the licensing pricing and revenue sharing models in a supply chain setting.Our findings indicate that,given a certain IoT platform service level,a manufacturer’s effort decreases as the relative weight decreases in the licensing pricing model.Additionally,when the platform’s effort cost is lower,the platform can invest more in compatibility,thereby improving the compatibility of smart devices.In such cases,the manufacturer can benefit from the platform’s incentives to exert compatibility efforts by reducing her efforts.We also identify two effects:the compatibility effect and the service value-added effect.When the relative weight of compatibility is small,the role of platform compatibility diminishes.Consequently,the platform cannot increase technology licensing fees to augment IoT service income,reducing profits.Our results also provide insights into how an IoT platform provider can strategically target a particular IoT service based on their cost characteristics and service level in smart device supply chains.
基金This work is supported by the Institute for Information&communications Technology Promotion(IITP)grant funded by the Korean government Ministry of Science and ICT(MSIT)(No.B0184-15-1001,Federated Interoperable Semantic IoT Testbeds and Applications).
文摘The Internet of Things(IoT)provides new opportunities for different IoT platforms connecting various devices together.The need to identify those devices is the foremost important to perform any kind of operation.Many organizations and standard bodies that provide specifications and frameworks for the IoT currently have their own identification mechanisms.Some existing industrial identification mechanisms can also be used in the IoT.There is no common Identification Scheme(IS)for the IoT as yet,because of the political and commercial differences amongst the standard bodies.The unavailability of a unified IS method makes the inter-working among IoT platforms challenging.This paper analyses and compares ISs used by several selected IoT platforms.This work will help in understanding the need for a common identification mechanism to provide inter-working among different IoT platforms.
文摘The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.
文摘Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.
