In 2021,12 fraudulent cases were identified in the Chinese carbon market.As a critical component of this emerging market,China’s carbon-credit scheme in the automotive sector faces several shortcomings,including info...In 2021,12 fraudulent cases were identified in the Chinese carbon market.As a critical component of this emerging market,China’s carbon-credit scheme in the automotive sector faces several shortcomings,including informational opacity and operational inefficiency,which affect market functionality and fairness.This study develops an information system that integrates blockchain technology and the Internet of Things to manage a carbon-credit scheme.Specifically,we attached carbon credits to each vehicle with radio frequency identification electronic tags and a chained data structure to ensure the traceability and reliability of information flow.We use the distributed ledger technology and establish five distinct types of smart contracts for decentralized operations to ensure that all procedures of the Chinese carboncredit scheme are standardized and under public scrutiny.The proposed infrastructure has the potential to significantly enhance the transparency and efficiency of China’s carbon-credit schemes.展开更多
The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These in...The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the critical issues, which is the prediction of fraudulent devices, i.e., adversaries, preferably as early as possible in the IoT. In this paper, a hybrid communication mechanism is presented where the Hidden Markov Model (HMM) predicts the legitimacy of the requesting device (both source and destination), and the Advanced Encryption Standard (AES) safeguards the reliability of the transmitted data over a shared communication medium, preferably through a secret shared key, i.e., , and timestamp information. A device becomes trusted if it has passed both evaluation levels, i.e., HMM and message decryption, within a stipulated time interval. The proposed hybrid, along with existing state-of-the-art approaches, has been simulated in the realistic environment of the IoT to verify the security measures. These evaluations were carried out in the presence of intruders capable of launching various attacks simultaneously, such as man-in-the-middle, device impersonations, and masquerading attacks. Moreover, the proposed approach has been proven to be more effective than existing state-of-the-art approaches due to its exceptional performance in communication, processing, and storage overheads, i.e., 13%, 19%, and 16%, respectively. Finally, the proposed hybrid approach is pruned against well-known security attacks in the IoT.展开更多
The integration of Artificial Intelligence (AI) and Internet of Things (IoT), known as AIoT, presents a transformative framework for modernizing campus IT operation and maintenance. This paper details the design of a ...The integration of Artificial Intelligence (AI) and Internet of Things (IoT), known as AIoT, presents a transformative framework for modernizing campus IT operation and maintenance. This paper details the design of a hierarchical AIoT architecture that leverages edge computing for real-time decision-making and cloud analytics for long-term optimization, achieving a higher system availability while reducing data transmission costs. The proposed system addresses critical challenges in traditional campus management such as energy inefficiency, reactive maintenance, and resource underutilization through intelligent applications like predictive resource allocation and environmental control. Furthermore, the design incorporates a robust, AI-driven cybersecurity framework and intelligent data processing paradigms, such as federated learning, which enhance maintenance efficiency and reduce false alarms. The transition to an AIoT-enabled campus is not merely a technological upgrade but a strategic shift towards a predictive, efficient, and sustainable operational model, fundamentally enhancing the management of university infrastructures.展开更多
In the Satellite-integrated Internet of Things(S-IoT),data freshness in the time-sensitive scenarios could not be guaranteed over the timevarying topology with current distribution strategies aiming to reduce the tran...In the Satellite-integrated Internet of Things(S-IoT),data freshness in the time-sensitive scenarios could not be guaranteed over the timevarying topology with current distribution strategies aiming to reduce the transmission delay.To address this problem,in this paper,we propose an age-optimal caching distribution mechanism for the high-timeliness data collection in S-IoT by adopting a freshness metric,as called age of information(AoI)through the caching-based single-source multidestinations(SSMDs)transmission,namely Multi-AoI,with a well-designed cross-slot directed graph(CSG).With the proposed CSG,we make optimizations on the locations of cache nodes by solving a nonlinear integer programming problem on minimizing Multi-AoI.In particular,we put up forward three specific algorithms respectively for improving the Multi-AoI,i.e.,the minimum queuing delay algorithm(MQDA)based on node deviation from average level,the minimum propagation delay algorithm(MPDA)based on the node propagation delay reduction,and a delay balanced algorithm(DBA)based on node deviation from average level and propagation delay reduction.The simulation results show that the proposed mechanism can effectively improve the freshness of information compared with the random selection algorithm.展开更多
Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both cus...Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare infrastructures.In addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,transmitting.Therefore,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled domains.In this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT infrastructures.Sliding window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission activity.Additionally,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s body.In contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of accuracy.Moreover,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the IoT.The proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information perspectives.Simulation and analytical results have proved that the proposed privacy-preserving information fusion technique for wearable devices is an ideal solution for resource-constrained infrastructures such as IoT and the Internet ofMedical Things,where both device privacy and information integrity are important.Finally,the proposed hybrid approach is proven against well-known intruder attacks,especially those related to the privacy of the respective device in IoT infrastructures.展开更多
The Internet of things(IoT)has become a key infrastructure providing up-to-date and fresh information for policy analysis and decision-making of upper-layer applications.However,there are limited sensing and communica...The Internet of things(IoT)has become a key infrastructure providing up-to-date and fresh information for policy analysis and decision-making of upper-layer applications.However,there are limited sensing and communication resources in IoT devices,which significantly affects the timeliness and freshness of the updated status.This work proposes two schemes,namely,the generation rate control and service rate reservation schemes,to improve the overall information freshness of multiple status update streams at the receiver.Specifically,using the recently proposed Age of Information(AoI)as the metric for evaluating information freshness,we characterized the overall information freshness,i.e.,the overall average AoI at the receiver for both schemes,by considering the urgency difference of status update and streams.Both schemes for status updates and streams,respectively,were formulated as two optimization problems.We proved that both problems are convex and the optimal generation and service rates for different streams are found by the standard convex optimization algorithm.Moreover,we proposed both approximate optimal generation and approximate optimal service rate for fast deployment in heavy and light load cases.Numerical results verify the theoretical findings and accuracy of the proposed approximate solutions,guiding the design and deployment of IoT.展开更多
As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for...As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for people to spread and share information.Nevertheless,SIoT is characterized by high openness and autonomy,multiple kinds of information can spread rapidly,freely and cooperatively in SIoT,which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its diffusion.To this end,with the aim of exploring multi-information cooperative diffusion processes in SIoT,we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this paper.Subsequently,the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated,and the diffusion trend is predicted.On this basis,to further control the multi-information cooperative diffusion process efficiently,we propose two control strategies for information diffusion with control objectives,develop an optimal control system for the multi-information cooperative diffusion process,and propose the corresponding optimal control method.The optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control theory.Finally,extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model,strategy and method.展开更多
There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computin...There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is proposed.In the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor nodes.The similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is proposed.According to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is proposed.The nodes are allocated according to the set pair similarity between nodes and different communities.Three-way community structures composed of a positive domain,boundary domain and negative domain are generated iteratively.Next,the overlapping node set is generated according to the calculation results of community node membership.Finally,experiments are carried out on artificial networks and real networks.The results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.展开更多
Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to over...Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to overburdened hospital systems,to dealing with the COVID-19 pandemic.However,despite considerable recent technological advances,the pace of successful implementation of promising IoT healthcare initiatives has been slow.To inspire more productive collaboration,we present here a simple—but surprisingly underrated—problemoriented approach to developing healthcare technologies.To further assist in this effort,we reviewed the various commercial,regulatory,social/cultural,and technological factors in the development of the IoT.We propose that fog computing—a technological paradigm wherein the burden of computing is shifted from a centralized cloud server closer to the data source—offers the greatest promise for building a robust and scalable healthcare IoT ecosystem.To this end,we explore the key enabling technologies that underpin the fog architecture,from the sensing layer all the way up to the cloud.It is our hope that ongoing advances in sensing,communications,cryptography,storage,machine learning,and artificial intelligence will be leveraged in meaningful ways to generate unprecedented medical intelligence and thus drive improvements in the health of many people.展开更多
A wireless search system was integrated on Windows 2000 server.Based on the communication principle between wireless data and Internet,the object expression of search file,the automatic query of document information,t...A wireless search system was integrated on Windows 2000 server.Based on the communication principle between wireless data and Internet,the object expression of search file,the automatic query of document information,the segment browsing of result information,and the receiving and sending of user information were realized by using Active Server Page 3.0,VB Script,WML Script insert languages and object orient database technology.The requirement querying information of material processing through Internet by GPRS,WAP mobile handset and so on was accomplished.展开更多
Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors.Quantifying the data freshness through age of information(AoI),in this paper,we jointly...Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors.Quantifying the data freshness through age of information(AoI),in this paper,we jointly design sampling and non-slot based scheduling policies to minimize the maximum time-average age of information(MAoI)among sensors with the constraints of average energy cost and finite queue stability.To overcome the intractability involving high couplings of such a complex stochastic process,we first focus on the single-sensor time-average AoI optimization problem and convert the constrained Markov decision process(CMDP)into an unconstrained Markov decision process(MDP)by the Lagrangian method.With the infinite-time average energy and AoI expression expended as the Bellman equation,the singlesensor time-average AoI optimization problem can be approached through the steady-state distribution probability.Further,we propose a low-complexity sub-optimal sampling and semi-distributed scheduling scheme for the multi-sensor scenario.The simulation results show that the proposed scheme reduces the MAoI significantly while achieving a balance between the sampling rate and service rate for multiple sensors.展开更多
The development of the Internet of Things(IoT)has brought great convenience to people.However,some information security problems such as privacy leakage are caused by communicating with risky users.It is a challenge t...The development of the Internet of Things(IoT)has brought great convenience to people.However,some information security problems such as privacy leakage are caused by communicating with risky users.It is a challenge to choose reliable users with which to interact in the IoT.Therefore,trust plays a crucial role in the IoT because trust may avoid some risks.Agents usually choose reliable users with high trust to maximize their own interests based on reinforcement learning.However,trust propagation is time-consuming,and trust changes with the interaction process in social networks.To track the dynamic changes in trust values,a dynamic trust inference algorithm named Dynamic Double DQN Trust(Dy-DDQNTrust)is proposed to predict the indirect trust values of two users without direct contact with each other.The proposed algorithm simulates the interactions among users by double DQN.Firstly,CurrentNet and TargetNet networks are used to select users for interaction.The users with high trust are chosen to interact in future iterations.Secondly,the trust value is updated dynamically until a reliable trust path is found according to the result of the interaction.Finally,the trust value between indirect users is inferred by aggregating the opinions from multiple users through a Modified Collaborative Filtering Averagebased Similarity(SMCFAvg)aggregation strategy.Experiments are carried out on the FilmTrust and the Epinions datasets.Compared with TidalTrust,MoleTrust,DDQNTrust,DyTrust and Dynamic Weighted Heuristic trust path Search algorithm(DWHS),our dynamic trust inference algorithm has higher prediction accuracy and better scalability.展开更多
Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reli...Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.展开更多
The existing systems sustained with the investments made require more automation and digital transformation with the continuous advancement of tech-nology.The aviation industry is a sector that is open to more automat...The existing systems sustained with the investments made require more automation and digital transformation with the continuous advancement of tech-nology.The aviation industry is a sector that is open to more automation and digi-tal transformation,mainly because of the intense competition and the analysis of a large variety of data.The long duration of operations in current airline processes and some processflows cause customer dissatisfaction and cost increase.In this study,the boarding process,which is one of the operational processes of airline transportation and is open to improvement,was discussed.The classical boarding process has been redesigned using Internet of Things technology a model called Boarding 4.0 was created.With Boarding 4.0,it is aimed to design a process where passengers can take their time before boarding more efficiently.In the study,the sub-processes of the Boarding 4.0 model,other processes that the sub-processes interact with,their activities,and data exchange passenger move-ments during the activities are explained in detail.Compared to the classical boarding process and Boarding 4.0 with the fuzzy ahp technique,it has been shown that boarding 4.0 is more advantageous and passenger movement times can be reduced during boarding.As a result of the evaluation made with the fuzzy ahp,it was determined that boarding 4.0 is more advantageous than the classical boarding process.In addition,when the total time of the sub-activities in the board-ing process is calculated,boarding activities for a passenger take 50 min with the classic boarding process and 20 min with Boarding 4.0.Thus,when Boarding 4.0 is used,the passenger gains 30 min.Furthermore,when the calculation is made concerning the airport’s current capacity,two passengers are hosted with the clas-sical boarding process,whilefive passengers are hosted with Boarding 4.0.This acquisition is significant for airports in terms of efficient use of resources.展开更多
The use of Internet of Things(IoT)applications become dominant in many systems.Its on-chip data processing and computations are also increasing consistently.The battery enabled and low leakage memory system at subthre...The use of Internet of Things(IoT)applications become dominant in many systems.Its on-chip data processing and computations are also increasing consistently.The battery enabled and low leakage memory system at subthreshold regime is a critical requirement for these IoT applications.The cache memory designed on Static Random-Access Memory(SRAM)cell with features such as low power,high speed,and process tolerance are highly important for the IoT memory system.Therefore,a process tolerant SRAM cell with low power,improved delay and better stability is presented in this research paper.The proposed cell comprises 11 transistors designed with symmetric approach for write operations and single ended circuit for read operations that exhibits an average dynamic power saving of 43.55%and 47.75%for write and 35.59%and 36.56%for read operations compared to 6 T and 8 T SRAM cells.The cell shows an improved write delay of 26.46%and 37.16%over 6 T and 8T and read delay is lowered by 50.64%and 72.90%against 6 T and 10 T cells.The symmetric design used in core latch to improve the write noise margin(WNM)by 17.78%and 6.67%whereas the single ended separate read circuit improves the Read Static Noise Margin(RSNM)by 1.88x and 0.33x compared to 6 T and 8T cells.The read power delay product and write power delay product are lower by 1.94x,1.39x and 0.17x,2.02x than 6 T and 8 T cells respectively.The lower variability from 5000 samples validates the robustness of the proposed cell.The simulations are carried out in Cadence virtuoso simulator tool with Generic Process Design Kit(GPDK)45 nm technology file in this work.展开更多
Based on analysis of the present situation and problems of course project of the Internet of Things engineering,we propose a relational integrated course project pattern around three levels of perception layer,network...Based on analysis of the present situation and problems of course project of the Internet of Things engineering,we propose a relational integrated course project pattern around three levels of perception layer,network layer,application layer of the Internet of Things system.The realization of a complete Internet of Things system is divided into three course projects to complete three key points,which may eventually make a complete system of things.Through the link among the three integrated course projects,knowledge of four years will be connected together and form an organic whole.We use a team performance and examination methods of the process-oriented examination,project paper and oral examination for the integrated course project in order to improve students’cooperation ability,expression ability,communication ability and other integrated quality.展开更多
Improving the information freshness is critical for the monitoring and controlling applications in the cellular Internet of Things(IoT).In this paper,we are interested in optimizing the bandwidth allocation dynamicall...Improving the information freshness is critical for the monitoring and controlling applications in the cellular Internet of Things(IoT).In this paper,we are interested in optimizing the bandwidth allocation dynamically to improve the information freshness of the short packet based uplink status updates,which is characterized by a recently proposed metric,age of information(Ao I).We first design a status update scheme with channel distribution information(CDI).By relaxing the hard bandwidth constraint and introducing a Lagrangian multiplier,we first decouple the multi-MTCD bandwidth allocation problem into a single MTCD Markov decision process(MDP).Under the MDP framework,after variable substitution,we obtain the single-MTCD status update scheme by solving a linear programming problem.Then,we adjust the Lagrangian multiplier to make the obtained scheme satisfy the relaxed bandwidth constraint.Finally,a greedy policy is built on the proposed scheme to adjust the bandwidth allocation in each slot to satisfy the hard bandwidth constraint.In the unknown environment without CDI,we further design a bandwidth allocation scheme which only maximizes the expected sum Ao I drop within each time slot.Simulation results show that in terms of AoI,the proposed schemes outperform the benchmark schemes.展开更多
In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for th...In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for the distribution network only considers the information reported by the Feeder Terminal Unit(FTU)and the fault tolerance rate is low when the information is omitted or misreported.Therefore,this study considers the influence of the distributed generations(DGs)for the distribution network.This takes the CEIAS as a redundant information source and solves the model by applying a binary particle swarm optimization algorithm(BPSO).The improved Dempster/S-hafer evidence theory(D-S evidence theory)is used for evidence fusion to achieve the fault section location for the distribution network.An example is provided to verify that the proposed method can achieve single or multiple fault locations with a higher fault tolerance.展开更多
The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this con...The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this context,age of information(AoI),as the metric of information freshness,gets more and more recognition,and simultaneously,the status packet blocklength plays an important role in improving the information freshness.In this work,we firstly consider a case with perfect channel state information(CSI)at the base station(BS),and derive the closed-form expression of the average AoI by using the Shannon theory.Guided by this,we obtain the tradeoff relationship among the status packet blocklength,transmission time and transmission failure probability.Accordingly,we optimize the status packet blocklength to minimize the average AoI.Then,we consider a more practical case with finite blocklength and imperfect CSI at the BS.In this case,we exploit pilot sequence to assist channel estimation,and derive an approximated closed-form expression of the average AoI according to short packet communication theory.It is found that increasing pilot block-length can improve the accuracy of channel estimation but reduce the frequency of status updates.Hence,we jointly optimize the pilot blocklength and status packet blocklength to improve the AoI performance.Extensive simulation results validate that the proposed methods can achieve almost the same performance as the exhaustive search methods.展开更多
As industrialization and informatization in China deeply integrate and the Internet of Things rapidly develops,industrial control systems are facing increasingly severe information security challenges.The industrial c...As industrialization and informatization in China deeply integrate and the Internet of Things rapidly develops,industrial control systems are facing increasingly severe information security challenges.The industrial control system of the gas extraction plant is characterized by numerous points and centralized operations,with a strong reliance on the system and stringent real-time requirements.展开更多
基金Financial support from the National Natural Science Foundation of China(under grants numbers:72271249 and 72432005)from Guangdong Basic and Applied Basic Research Foundation(under grant number:2023B1515040001)are highly appreciated.
文摘In 2021,12 fraudulent cases were identified in the Chinese carbon market.As a critical component of this emerging market,China’s carbon-credit scheme in the automotive sector faces several shortcomings,including informational opacity and operational inefficiency,which affect market functionality and fairness.This study develops an information system that integrates blockchain technology and the Internet of Things to manage a carbon-credit scheme.Specifically,we attached carbon credits to each vehicle with radio frequency identification electronic tags and a chained data structure to ensure the traceability and reliability of information flow.We use the distributed ledger technology and establish five distinct types of smart contracts for decentralized operations to ensure that all procedures of the Chinese carboncredit scheme are standardized and under public scrutiny.The proposed infrastructure has the potential to significantly enhance the transparency and efficiency of China’s carbon-credit schemes.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University via Grant No.(QU-APC-2025).
文摘The Internet of Things (IoT) and edge-assisted networking infrastructures are capable of bringing data processing and accessibility services locally at the respective edge rather than at a centralized module. These infrastructures are very effective in providing a fast response to the respective queries of the requesting modules, but their distributed nature has introduced other problems such as security and privacy. To address these problems, various security-assisted communication mechanisms have been developed to safeguard every active module, i.e., devices and edges, from every possible vulnerability in the IoT. However, these methodologies have neglected one of the critical issues, which is the prediction of fraudulent devices, i.e., adversaries, preferably as early as possible in the IoT. In this paper, a hybrid communication mechanism is presented where the Hidden Markov Model (HMM) predicts the legitimacy of the requesting device (both source and destination), and the Advanced Encryption Standard (AES) safeguards the reliability of the transmitted data over a shared communication medium, preferably through a secret shared key, i.e., , and timestamp information. A device becomes trusted if it has passed both evaluation levels, i.e., HMM and message decryption, within a stipulated time interval. The proposed hybrid, along with existing state-of-the-art approaches, has been simulated in the realistic environment of the IoT to verify the security measures. These evaluations were carried out in the presence of intruders capable of launching various attacks simultaneously, such as man-in-the-middle, device impersonations, and masquerading attacks. Moreover, the proposed approach has been proven to be more effective than existing state-of-the-art approaches due to its exceptional performance in communication, processing, and storage overheads, i.e., 13%, 19%, and 16%, respectively. Finally, the proposed hybrid approach is pruned against well-known security attacks in the IoT.
文摘The integration of Artificial Intelligence (AI) and Internet of Things (IoT), known as AIoT, presents a transformative framework for modernizing campus IT operation and maintenance. This paper details the design of a hierarchical AIoT architecture that leverages edge computing for real-time decision-making and cloud analytics for long-term optimization, achieving a higher system availability while reducing data transmission costs. The proposed system addresses critical challenges in traditional campus management such as energy inefficiency, reactive maintenance, and resource underutilization through intelligent applications like predictive resource allocation and environmental control. Furthermore, the design incorporates a robust, AI-driven cybersecurity framework and intelligent data processing paradigms, such as federated learning, which enhance maintenance efficiency and reduce false alarms. The transition to an AIoT-enabled campus is not merely a technological upgrade but a strategic shift towards a predictive, efficient, and sustainable operational model, fundamentally enhancing the management of university infrastructures.
基金supports from the Major Key Project of PCL (PCL2021A031)Shenzhen Science Technology Program (GXWD20201230155427003-20200824093323001)
文摘In the Satellite-integrated Internet of Things(S-IoT),data freshness in the time-sensitive scenarios could not be guaranteed over the timevarying topology with current distribution strategies aiming to reduce the transmission delay.To address this problem,in this paper,we propose an age-optimal caching distribution mechanism for the high-timeliness data collection in S-IoT by adopting a freshness metric,as called age of information(AoI)through the caching-based single-source multidestinations(SSMDs)transmission,namely Multi-AoI,with a well-designed cross-slot directed graph(CSG).With the proposed CSG,we make optimizations on the locations of cache nodes by solving a nonlinear integer programming problem on minimizing Multi-AoI.In particular,we put up forward three specific algorithms respectively for improving the Multi-AoI,i.e.,the minimum queuing delay algorithm(MQDA)based on node deviation from average level,the minimum propagation delay algorithm(MPDA)based on the node propagation delay reduction,and a delay balanced algorithm(DBA)based on node deviation from average level and propagation delay reduction.The simulation results show that the proposed mechanism can effectively improve the freshness of information compared with the random selection algorithm.
基金Ministry of Higher Education of Malaysia under the Research GrantLRGS/1/2019/UKM-UKM/5/2 and Princess Nourah bint Abdulrahman University for financing this researcher through Supporting Project Number(PNURSP2024R235),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare infrastructures.In addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,transmitting.Therefore,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled domains.In this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT infrastructures.Sliding window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission activity.Additionally,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s body.In contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of accuracy.Moreover,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the IoT.The proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information perspectives.Simulation and analytical results have proved that the proposed privacy-preserving information fusion technique for wearable devices is an ideal solution for resource-constrained infrastructures such as IoT and the Internet ofMedical Things,where both device privacy and information integrity are important.Finally,the proposed hybrid approach is proven against well-known intruder attacks,especially those related to the privacy of the respective device in IoT infrastructures.
基金sponsored by the National Natural Science Foundation of China under Grant 61901066,Grant 61971077sponsored by Natural Science Foundation of Chongqing,China under Grant cstc2019jcyjmsxmX0575,Grant cstc2021jcyj-msxmX0458+2 种基金in part by the Entrepreneurship and Innovation Support Plan of Chongqing for Returned Overseas Scholars under Grant cx2021092supported by the open research fund of National Mobile Communications Research Laboratory,Southeast University(No.2021D13,No.2022D06)the Industrial Internet innovation and development project(No.TC200A00M).
文摘The Internet of things(IoT)has become a key infrastructure providing up-to-date and fresh information for policy analysis and decision-making of upper-layer applications.However,there are limited sensing and communication resources in IoT devices,which significantly affects the timeliness and freshness of the updated status.This work proposes two schemes,namely,the generation rate control and service rate reservation schemes,to improve the overall information freshness of multiple status update streams at the receiver.Specifically,using the recently proposed Age of Information(AoI)as the metric for evaluating information freshness,we characterized the overall information freshness,i.e.,the overall average AoI at the receiver for both schemes,by considering the urgency difference of status update and streams.Both schemes for status updates and streams,respectively,were formulated as two optimization problems.We proved that both problems are convex and the optimal generation and service rates for different streams are found by the standard convex optimization algorithm.Moreover,we proposed both approximate optimal generation and approximate optimal service rate for fast deployment in heavy and light load cases.Numerical results verify the theoretical findings and accuracy of the proposed approximate solutions,guiding the design and deployment of IoT.
基金supported by the National Natural Science Foundation of China(Grant Nos.62102240,62071283)the China Postdoctoral Science Foundation(Grant No.2020M683421)the Key R&D Program of Shaanxi Province(Grant No.2020ZDLGY10-05).
文摘As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for people to spread and share information.Nevertheless,SIoT is characterized by high openness and autonomy,multiple kinds of information can spread rapidly,freely and cooperatively in SIoT,which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its diffusion.To this end,with the aim of exploring multi-information cooperative diffusion processes in SIoT,we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this paper.Subsequently,the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated,and the diffusion trend is predicted.On this basis,to further control the multi-information cooperative diffusion process efficiently,we propose two control strategies for information diffusion with control objectives,develop an optimal control system for the multi-information cooperative diffusion process,and propose the corresponding optimal control method.The optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control theory.Finally,extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model,strategy and method.
文摘There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is proposed.In the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor nodes.The similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is proposed.According to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is proposed.The nodes are allocated according to the set pair similarity between nodes and different communities.Three-way community structures composed of a positive domain,boundary domain and negative domain are generated iteratively.Next,the overlapping node set is generated according to the calculation results of community node membership.Finally,experiments are carried out on artificial networks and real networks.The results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.
基金supported in part by a grant from the Victoria-Jiangsu Program for Technology and Innovation Research and Development。
文摘Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to overburdened hospital systems,to dealing with the COVID-19 pandemic.However,despite considerable recent technological advances,the pace of successful implementation of promising IoT healthcare initiatives has been slow.To inspire more productive collaboration,we present here a simple—but surprisingly underrated—problemoriented approach to developing healthcare technologies.To further assist in this effort,we reviewed the various commercial,regulatory,social/cultural,and technological factors in the development of the IoT.We propose that fog computing—a technological paradigm wherein the burden of computing is shifted from a centralized cloud server closer to the data source—offers the greatest promise for building a robust and scalable healthcare IoT ecosystem.To this end,we explore the key enabling technologies that underpin the fog architecture,from the sensing layer all the way up to the cloud.It is our hope that ongoing advances in sensing,communications,cryptography,storage,machine learning,and artificial intelligence will be leveraged in meaningful ways to generate unprecedented medical intelligence and thus drive improvements in the health of many people.
基金Item Sponsored by Doctoral Program of Higher Education of China(97014515)
文摘A wireless search system was integrated on Windows 2000 server.Based on the communication principle between wireless data and Internet,the object expression of search file,the automatic query of document information,the segment browsing of result information,and the receiving and sending of user information were realized by using Active Server Page 3.0,VB Script,WML Script insert languages and object orient database technology.The requirement querying information of material processing through Internet by GPRS,WAP mobile handset and so on was accomplished.
基金supported in part by the National Key R&D Program of China(No.2021YFB3300100)the National Natural Science Foundation of China(No.62171062)。
文摘Effective control of time-sensitive industrial applications depends on the real-time transmission of data from underlying sensors.Quantifying the data freshness through age of information(AoI),in this paper,we jointly design sampling and non-slot based scheduling policies to minimize the maximum time-average age of information(MAoI)among sensors with the constraints of average energy cost and finite queue stability.To overcome the intractability involving high couplings of such a complex stochastic process,we first focus on the single-sensor time-average AoI optimization problem and convert the constrained Markov decision process(CMDP)into an unconstrained Markov decision process(MDP)by the Lagrangian method.With the infinite-time average energy and AoI expression expended as the Bellman equation,the singlesensor time-average AoI optimization problem can be approached through the steady-state distribution probability.Further,we propose a low-complexity sub-optimal sampling and semi-distributed scheduling scheme for the multi-sensor scenario.The simulation results show that the proposed scheme reduces the MAoI significantly while achieving a balance between the sampling rate and service rate for multiple sensors.
基金supported by the National Natural Science Foundation of China(62072392)the National Natural Science Foundation of China(61972360)the Major Scientific and Technological Innovation Projects of Shandong Province(2019522Y020131).
文摘The development of the Internet of Things(IoT)has brought great convenience to people.However,some information security problems such as privacy leakage are caused by communicating with risky users.It is a challenge to choose reliable users with which to interact in the IoT.Therefore,trust plays a crucial role in the IoT because trust may avoid some risks.Agents usually choose reliable users with high trust to maximize their own interests based on reinforcement learning.However,trust propagation is time-consuming,and trust changes with the interaction process in social networks.To track the dynamic changes in trust values,a dynamic trust inference algorithm named Dynamic Double DQN Trust(Dy-DDQNTrust)is proposed to predict the indirect trust values of two users without direct contact with each other.The proposed algorithm simulates the interactions among users by double DQN.Firstly,CurrentNet and TargetNet networks are used to select users for interaction.The users with high trust are chosen to interact in future iterations.Secondly,the trust value is updated dynamically until a reliable trust path is found according to the result of the interaction.Finally,the trust value between indirect users is inferred by aggregating the opinions from multiple users through a Modified Collaborative Filtering Averagebased Similarity(SMCFAvg)aggregation strategy.Experiments are carried out on the FilmTrust and the Epinions datasets.Compared with TidalTrust,MoleTrust,DDQNTrust,DyTrust and Dynamic Weighted Heuristic trust path Search algorithm(DWHS),our dynamic trust inference algorithm has higher prediction accuracy and better scalability.
基金supported by Science and Technology Project of China Southern Power Grid Company Limited under Grant Number 036000KK52200058(GDKJXM20202001).
文摘Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.
文摘The existing systems sustained with the investments made require more automation and digital transformation with the continuous advancement of tech-nology.The aviation industry is a sector that is open to more automation and digi-tal transformation,mainly because of the intense competition and the analysis of a large variety of data.The long duration of operations in current airline processes and some processflows cause customer dissatisfaction and cost increase.In this study,the boarding process,which is one of the operational processes of airline transportation and is open to improvement,was discussed.The classical boarding process has been redesigned using Internet of Things technology a model called Boarding 4.0 was created.With Boarding 4.0,it is aimed to design a process where passengers can take their time before boarding more efficiently.In the study,the sub-processes of the Boarding 4.0 model,other processes that the sub-processes interact with,their activities,and data exchange passenger move-ments during the activities are explained in detail.Compared to the classical boarding process and Boarding 4.0 with the fuzzy ahp technique,it has been shown that boarding 4.0 is more advantageous and passenger movement times can be reduced during boarding.As a result of the evaluation made with the fuzzy ahp,it was determined that boarding 4.0 is more advantageous than the classical boarding process.In addition,when the total time of the sub-activities in the board-ing process is calculated,boarding activities for a passenger take 50 min with the classic boarding process and 20 min with Boarding 4.0.Thus,when Boarding 4.0 is used,the passenger gains 30 min.Furthermore,when the calculation is made concerning the airport’s current capacity,two passengers are hosted with the clas-sical boarding process,whilefive passengers are hosted with Boarding 4.0.This acquisition is significant for airports in terms of efficient use of resources.
文摘The use of Internet of Things(IoT)applications become dominant in many systems.Its on-chip data processing and computations are also increasing consistently.The battery enabled and low leakage memory system at subthreshold regime is a critical requirement for these IoT applications.The cache memory designed on Static Random-Access Memory(SRAM)cell with features such as low power,high speed,and process tolerance are highly important for the IoT memory system.Therefore,a process tolerant SRAM cell with low power,improved delay and better stability is presented in this research paper.The proposed cell comprises 11 transistors designed with symmetric approach for write operations and single ended circuit for read operations that exhibits an average dynamic power saving of 43.55%and 47.75%for write and 35.59%and 36.56%for read operations compared to 6 T and 8 T SRAM cells.The cell shows an improved write delay of 26.46%and 37.16%over 6 T and 8T and read delay is lowered by 50.64%and 72.90%against 6 T and 10 T cells.The symmetric design used in core latch to improve the write noise margin(WNM)by 17.78%and 6.67%whereas the single ended separate read circuit improves the Read Static Noise Margin(RSNM)by 1.88x and 0.33x compared to 6 T and 8T cells.The read power delay product and write power delay product are lower by 1.94x,1.39x and 0.17x,2.02x than 6 T and 8 T cells respectively.The lower variability from 5000 samples validates the robustness of the proposed cell.The simulations are carried out in Cadence virtuoso simulator tool with Generic Process Design Kit(GPDK)45 nm technology file in this work.
文摘Based on analysis of the present situation and problems of course project of the Internet of Things engineering,we propose a relational integrated course project pattern around three levels of perception layer,network layer,application layer of the Internet of Things system.The realization of a complete Internet of Things system is divided into three course projects to complete three key points,which may eventually make a complete system of things.Through the link among the three integrated course projects,knowledge of four years will be connected together and form an organic whole.We use a team performance and examination methods of the process-oriented examination,project paper and oral examination for the integrated course project in order to improve students’cooperation ability,expression ability,communication ability and other integrated quality.
基金supported by the Natural Science Foundations of China under Grant(62171464,62171461)the National Key R&D Program of China(No.11112018YFB1801103)the Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu under Grant BK20212001。
文摘Improving the information freshness is critical for the monitoring and controlling applications in the cellular Internet of Things(IoT).In this paper,we are interested in optimizing the bandwidth allocation dynamically to improve the information freshness of the short packet based uplink status updates,which is characterized by a recently proposed metric,age of information(Ao I).We first design a status update scheme with channel distribution information(CDI).By relaxing the hard bandwidth constraint and introducing a Lagrangian multiplier,we first decouple the multi-MTCD bandwidth allocation problem into a single MTCD Markov decision process(MDP).Under the MDP framework,after variable substitution,we obtain the single-MTCD status update scheme by solving a linear programming problem.Then,we adjust the Lagrangian multiplier to make the obtained scheme satisfy the relaxed bandwidth constraint.Finally,a greedy policy is built on the proposed scheme to adjust the bandwidth allocation in each slot to satisfy the hard bandwidth constraint.In the unknown environment without CDI,we further design a bandwidth allocation scheme which only maximizes the expected sum Ao I drop within each time slot.Simulation results show that in terms of AoI,the proposed schemes outperform the benchmark schemes.
基金supported by the Science and Technology Project of State Grid Shandong Electric Power Company?“Research on the Data-Driven Method for Energy Internet”?(Project No.2018A-100)。
文摘In order to promote the development of the Internet of Things(IoT),there has been an increase in the coverage of the customer electric information acquisition system(CEIAS).The traditional fault location method for the distribution network only considers the information reported by the Feeder Terminal Unit(FTU)and the fault tolerance rate is low when the information is omitted or misreported.Therefore,this study considers the influence of the distributed generations(DGs)for the distribution network.This takes the CEIAS as a redundant information source and solves the model by applying a binary particle swarm optimization algorithm(BPSO).The improved Dempster/S-hafer evidence theory(D-S evidence theory)is used for evidence fusion to achieve the fault section location for the distribution network.An example is provided to verify that the proposed method can achieve single or multiple fault locations with a higher fault tolerance.
基金supported by National Natural Science Foundation of China (Grants No. 62122094 and No.62171464)
文摘The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this context,age of information(AoI),as the metric of information freshness,gets more and more recognition,and simultaneously,the status packet blocklength plays an important role in improving the information freshness.In this work,we firstly consider a case with perfect channel state information(CSI)at the base station(BS),and derive the closed-form expression of the average AoI by using the Shannon theory.Guided by this,we obtain the tradeoff relationship among the status packet blocklength,transmission time and transmission failure probability.Accordingly,we optimize the status packet blocklength to minimize the average AoI.Then,we consider a more practical case with finite blocklength and imperfect CSI at the BS.In this case,we exploit pilot sequence to assist channel estimation,and derive an approximated closed-form expression of the average AoI according to short packet communication theory.It is found that increasing pilot block-length can improve the accuracy of channel estimation but reduce the frequency of status updates.Hence,we jointly optimize the pilot blocklength and status packet blocklength to improve the AoI performance.Extensive simulation results validate that the proposed methods can achieve almost the same performance as the exhaustive search methods.
文摘As industrialization and informatization in China deeply integrate and the Internet of Things rapidly develops,industrial control systems are facing increasingly severe information security challenges.The industrial control system of the gas extraction plant is characterized by numerous points and centralized operations,with a strong reliance on the system and stringent real-time requirements.
