In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and ca...In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and cannot achieve full-automatic migration. In other words, when the server overload requires the administrator to artificially select a low-load host, and then hit migration command to implement the migration. In recent years, the Hadoop is becoming popular, and the read performance of the data is measured in terms of the time overhead for reading the required data. The key to reducing read time is to optimize that Hadoop cloud data read time and the RDBMS data query time. This paper integrates the mentioned techniques to construct the novel JavaEE enterprise development pattern that will promote the further development of the related techniques.展开更多
Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabli...Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabling updates and retrievals of ciphertext on untrusted cloud server while ensuring data privacy.However,previous research on DSSE mostly focused on single keyword search,which limits its practical application in cloud-based IoT systems.Recently,Patranabis(NDSS 2021)[1]proposed a groundbreaking DSSE scheme for conjunctive keyword search.However,this scheme fails to effectively handle deletion operations in certain circumstances,resulting in inaccurate query results.Additionally,the scheme introduces unnecessary search overhead.To overcome these problems,we present CKSE,an efficient conjunctive keyword DSSE scheme.Our scheme improves the oblivious shared computation protocol used in the scheme of Patranabis,thus enabling a more comprehensive deletion functionality.Furthermore,we introduce a state chain structure to reduce the search overhead.Through security analysis and experimental evaluation,we demonstrate that our CKSE achieves more comprehensive deletion functionality while maintaining comparable search performance and security,compared to the oblivious dynamic cross-tags protocol of Patranabis.The combination of comprehensive functionality,high efficiency,and security makes our CKSE an ideal choice for deployment in cloud-based IoT systems.展开更多
In the cloud era, the control objects are becoming larger and the information processing is more complex, and it is difficult for traditional control systems to process massive data in a timely manner. In view of the ...In the cloud era, the control objects are becoming larger and the information processing is more complex, and it is difficult for traditional control systems to process massive data in a timely manner. In view of the difficulty of data processing in the cloud era, it is extremely important to perform massive data operations through cloud servers. Unmanned aeriel vehicle(UAV) control is the representative of the intelligent field. Based on the ant colony algorithm and incorporating the potential field method, an improved potential field ant colony algorithm is designed. To deal with the path planning problem of UAVs, the potential field ant colony algorithm shortens the optimal path distance by 6.7%, increases the algorithm running time by39.3%, and increases the maximum distance by 24.1% compared with the previous improvement. The cloud server is used to process the path problem of the UAV and feedback the calculation results in real time. Simulation experiments verify the effectiveness of the new algorithm in the cloud environment.展开更多
In this paper, we proposed a campus equipment ubiquitous-management system which is based on a genetic algorithm approach in cloud server. The system uses radio frequency identification （RFID） to monitor the status ...In this paper, we proposed a campus equipment ubiquitous-management system which is based on a genetic algorithm approach in cloud server. The system uses radio frequency identification （RFID） to monitor the status of equipment in real time, and uses wire or wireless network to send real-time situation to display on manager＇s PC or PDA. In addition, the system will also synchronize with database to record and reserve message. Furthermore, the status will display not only to a single manager but also a number of managers. In order to increase efficiency between graphical user interface （GUI） and database, the system adopts SqlDependency object of ADO.NET so that any changed situation of the database could be known immediately and synchronized with manager＇s PC or PDA. Because the problem of the equipment utilization is an NP-complete （non-deterministic polynomial） problem, we apply genetic algorithm to enhance the efficiency of finding optimum solution for equipment utilization. We assign constraints into the system, and the system will post back the optimum solution simultaneously on the screen. As a consequence, we compare our genetic algorithm based approach （GA） with the simulated annealing based approach （SA） for maximizing the equipment utilization. Experimental result shows that our GA approach achieves an average 79.66% improvement in equipment utilization in an acceptable run time.展开更多
The data in the cloud is protected by various mechanisms to ensure security aspects and user’s privacy.But,deceptive attacks like phishing might obtain the user’s data and use it for malicious purposes.In Spite of m...The data in the cloud is protected by various mechanisms to ensure security aspects and user’s privacy.But,deceptive attacks like phishing might obtain the user’s data and use it for malicious purposes.In Spite of much techno-logical advancement,phishing acts as thefirst step in a series of attacks.With technological advancements,availability and access to the phishing kits has improved drastically,thus making it an ideal tool for the hackers to execute the attacks.The phishing cases indicate use of foreign characters to disguise the ori-ginal Uniform Resource Locator(URL),typosquatting the popular domain names,using reserved characters for re directions and multi-chain phishing.Such phishing URLs can be stored as a part of the document and uploaded in the cloud,providing a nudge to hackers in cloud storage.The cloud servers are becoming the trusted tool for executing these attacks.The prevailing software for blacklisting phishing URLs lacks the security for multi-level phishing and expects security from the client’s end(browser).At the same time,the avalanche effect and immut-ability of block-chain proves to be a strong source of security.Considering these trends in technology,a block-chain basedfiltering implementation for preserving the integrity of user data stored in the cloud is proposed.The proposed Phish Block detects the homographic phishing URLs with accuracy of 91%which assures the security in cloud storage.展开更多
Power Station(PS)monitoring systems are becoming critical,ensuring electrical safety through early warning,and in the event of a PS fault,the power supply is quickly disconnected.Traditional technologies are based on ...Power Station(PS)monitoring systems are becoming critical,ensuring electrical safety through early warning,and in the event of a PS fault,the power supply is quickly disconnected.Traditional technologies are based on relays and don’t have a way to capture and store user data when there is a problem.The proposed framework is designed with the goal of providing smart environments for protecting electrical types of equipment.This paper proposes an Internet of Things(IoT)-based Smart Framework(SF)for monitoring the Power Devices(PD)which are being used in power substations.A Real-Time Monitoring(RTM)system is proposed,and it uses a state-of-the-art smart IoT-based System on Chip(SoC)sensors,a Hybrid Prediction Model(HPM),and it is being used in Big Data Processing(BDP).The Cloud Server(CS)processes the data and does the data analytics by comparing it with the historical data already stored in the CS.No-Structural Query Language Mongo Data Base(MDB)is used to store Sensor Data(SD)from the PSs.The proposed HPM combines the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)-algorithm for Outlier Detection(OD)and the Random Forest(RF)classification algorithm for removing the outlier SD and providing Fault Detection(FD)when the PD isn’t working.The suggested work is assessed and tested under various fault circumstances that happened in PSs.The simulation outcome proves that the proposed model is effective in monitoring the smooth functioning of the PS.Also,the suggested HPM has a higher Fault Prediction(FP)accuracy.This means that faults can be found earlier,early warning signals can be sent,and the power supply can be turned off quickly to ensure electrical safety.A powerful RTM and event warning system can also be built into the system before faults happen.展开更多
Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise.Moreover,it is widely utilizing for preventing injuries of athletes during a practice session and in few cas...Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise.Moreover,it is widely utilizing for preventing injuries of athletes during a practice session and in few cases,it leads to muscle fatigue.At present,emerging technology like the internet of things(IoT)and sensors is empowering to monitor and visualize the physical data from any remote location through internet connectivity.In this study,an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram(sEMG)sensor.Normally,the EMG signal is utilized to display muscle activity.Arduino controller,Wi-Fi module,and EMG sensor are utilized in developing the wearable device.The Time-frequency domain spectrum technique is employed for classifying the threemuscle fatigue conditions including meanRMS,mean frequency,etc.A real-time experiment is realized on six different individuals with developed wearable devices and the average RMS value assists to determine the average threshold of recorded data.The threshold level is analyzed by calculating the mean RMS value and concluded three fatigue conditions as>2V:Extensive);1–2V:Moderate,and<1V:relaxed.The warning alarm system was designed in LabVIEW with three color LEDs to indicate the different states of muscle fatigue.Moreover,the device is interfaced with the cloud through the internet provided with a Wi-Fi module embedded in wearable devices.The data available in the cloud server can be utilized for forecasting the frequency of an individual to muscle fatigue.展开更多
This paper analyzes the efficiency and security of bi- linear-map-based schemes and brings about an AAA based publicly auditable scheme for cloud computing, which is much more efficient. In this scheme, a trust model ...This paper analyzes the efficiency and security of bi- linear-map-based schemes and brings about an AAA based publicly auditable scheme for cloud computing, which is much more efficient. In this scheme, a trust model including four entities is designed to provide both integrity and confidentiality protection. The proposed scheme can be proved to achieve the security goals that no cheating cloud server can pass the auditing without storing users＇ data intact. The efficiency of the proposal is evaluated by analyzing the fulfillment of the design goals, including the computation cost, communication cost and storage cost of our scheme. This light weight publicly auditable Proof-of-storage scheme achieves security goals perfectly, and has an excellent efficiency performance superior to the current bilinear-map-based publicly auditable Proof-of-storage scheme.展开更多
With the increasing importance of cloud services worldwide, the cloud infrastructure and platform management has become critical for cloud service providers. In this paper, a novel architecture of intelligent server m...With the increasing importance of cloud services worldwide, the cloud infrastructure and platform management has become critical for cloud service providers. In this paper, a novel architecture of intelligent server management framework is proposed. In this framework, the communication layer is based on the Extensible Messaging and Presence Protocol (XMPP), which was developed for instant messaging and has been proven to be highly mature and suitable for mobile and large scalable deployment due to its extensibility and efficiency. The proposed architecture can simplify server management and increase flexibility and scalability when managing hundreds of thousands of servers in the cloud era.展开更多
This paper considers the collaborative resource allocation problem over a hybrid cloud center and edge server network, an emerging infrastructure for efficient Internet services. The cloud center acts as a pool of ine...This paper considers the collaborative resource allocation problem over a hybrid cloud center and edge server network, an emerging infrastructure for efficient Internet services. The cloud center acts as a pool of inexhaustible computation and storage powers. The edge servers often have limited computation and storage powers but are able to provide quick responses to service requests from end users. Upon receiving service requests, edge servers assign them to themselves, their neighboring edge servers, as well as the cloud center, aiming at minimizing the overall network cost. This paper first establishes an optimization model for this problem. Second, in light of the separable structure of the optimization model, we utilize the alternating direction method of multipliers （ADMM） to develop a fully collaborative resource allocation algorithm. The edge servers and the cloud center autonomously collaborate to compute their local optimization variables and prices of network resources, and reach an optimal solution. Numerical experiments demonstrate the effectiveness of the hybrid network infrastructure as well as the proposed algorithm.展开更多
文摘In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and cannot achieve full-automatic migration. In other words, when the server overload requires the administrator to artificially select a low-load host, and then hit migration command to implement the migration. In recent years, the Hadoop is becoming popular, and the read performance of the data is measured in terms of the time overhead for reading the required data. The key to reducing read time is to optimize that Hadoop cloud data read time and the RDBMS data query time. This paper integrates the mentioned techniques to construct the novel JavaEE enterprise development pattern that will promote the further development of the related techniques.
基金supported in part by the Major Science and Technology Projects in Yunnan Province(202202AD080013)King Khalid University for funding this work through Large Group Project under grant number RGP.2/373/45.
文摘Data privacy leakage has always been a critical concern in cloud-based Internet of Things(IoT)systems.Dynamic Symmetric Searchable Encryption(DSSE)with forward and backward privacy aims to address this issue by enabling updates and retrievals of ciphertext on untrusted cloud server while ensuring data privacy.However,previous research on DSSE mostly focused on single keyword search,which limits its practical application in cloud-based IoT systems.Recently,Patranabis(NDSS 2021)[1]proposed a groundbreaking DSSE scheme for conjunctive keyword search.However,this scheme fails to effectively handle deletion operations in certain circumstances,resulting in inaccurate query results.Additionally,the scheme introduces unnecessary search overhead.To overcome these problems,we present CKSE,an efficient conjunctive keyword DSSE scheme.Our scheme improves the oblivious shared computation protocol used in the scheme of Patranabis,thus enabling a more comprehensive deletion functionality.Furthermore,we introduce a state chain structure to reduce the search overhead.Through security analysis and experimental evaluation,we demonstrate that our CKSE achieves more comprehensive deletion functionality while maintaining comparable search performance and security,compared to the oblivious dynamic cross-tags protocol of Patranabis.The combination of comprehensive functionality,high efficiency,and security makes our CKSE an ideal choice for deployment in cloud-based IoT systems.
基金supported by the Natural Science Foundation of Heilongjiang Province (LH2021E045)。
文摘In the cloud era, the control objects are becoming larger and the information processing is more complex, and it is difficult for traditional control systems to process massive data in a timely manner. In view of the difficulty of data processing in the cloud era, it is extremely important to perform massive data operations through cloud servers. Unmanned aeriel vehicle(UAV) control is the representative of the intelligent field. Based on the ant colony algorithm and incorporating the potential field method, an improved potential field ant colony algorithm is designed. To deal with the path planning problem of UAVs, the potential field ant colony algorithm shortens the optimal path distance by 6.7%, increases the algorithm running time by39.3%, and increases the maximum distance by 24.1% compared with the previous improvement. The cloud server is used to process the path problem of the UAV and feedback the calculation results in real time. Simulation experiments verify the effectiveness of the new algorithm in the cloud environment.
文摘In this paper, we proposed a campus equipment ubiquitous-management system which is based on a genetic algorithm approach in cloud server. The system uses radio frequency identification （RFID） to monitor the status of equipment in real time, and uses wire or wireless network to send real-time situation to display on manager＇s PC or PDA. In addition, the system will also synchronize with database to record and reserve message. Furthermore, the status will display not only to a single manager but also a number of managers. In order to increase efficiency between graphical user interface （GUI） and database, the system adopts SqlDependency object of ADO.NET so that any changed situation of the database could be known immediately and synchronized with manager＇s PC or PDA. Because the problem of the equipment utilization is an NP-complete （non-deterministic polynomial） problem, we apply genetic algorithm to enhance the efficiency of finding optimum solution for equipment utilization. We assign constraints into the system, and the system will post back the optimum solution simultaneously on the screen. As a consequence, we compare our genetic algorithm based approach （GA） with the simulated annealing based approach （SA） for maximizing the equipment utilization. Experimental result shows that our GA approach achieves an average 79.66% improvement in equipment utilization in an acceptable run time.
文摘The data in the cloud is protected by various mechanisms to ensure security aspects and user’s privacy.But,deceptive attacks like phishing might obtain the user’s data and use it for malicious purposes.In Spite of much techno-logical advancement,phishing acts as thefirst step in a series of attacks.With technological advancements,availability and access to the phishing kits has improved drastically,thus making it an ideal tool for the hackers to execute the attacks.The phishing cases indicate use of foreign characters to disguise the ori-ginal Uniform Resource Locator(URL),typosquatting the popular domain names,using reserved characters for re directions and multi-chain phishing.Such phishing URLs can be stored as a part of the document and uploaded in the cloud,providing a nudge to hackers in cloud storage.The cloud servers are becoming the trusted tool for executing these attacks.The prevailing software for blacklisting phishing URLs lacks the security for multi-level phishing and expects security from the client’s end(browser).At the same time,the avalanche effect and immut-ability of block-chain proves to be a strong source of security.Considering these trends in technology,a block-chain basedfiltering implementation for preserving the integrity of user data stored in the cloud is proposed.The proposed Phish Block detects the homographic phishing URLs with accuracy of 91%which assures the security in cloud storage.
基金The authors are grateful to the Taif University Researchers Supporting Project Number(TURSP-2020/36),Taif University,Taif,Saudi Arabia.
文摘Power Station(PS)monitoring systems are becoming critical,ensuring electrical safety through early warning,and in the event of a PS fault,the power supply is quickly disconnected.Traditional technologies are based on relays and don’t have a way to capture and store user data when there is a problem.The proposed framework is designed with the goal of providing smart environments for protecting electrical types of equipment.This paper proposes an Internet of Things(IoT)-based Smart Framework(SF)for monitoring the Power Devices(PD)which are being used in power substations.A Real-Time Monitoring(RTM)system is proposed,and it uses a state-of-the-art smart IoT-based System on Chip(SoC)sensors,a Hybrid Prediction Model(HPM),and it is being used in Big Data Processing(BDP).The Cloud Server(CS)processes the data and does the data analytics by comparing it with the historical data already stored in the CS.No-Structural Query Language Mongo Data Base(MDB)is used to store Sensor Data(SD)from the PSs.The proposed HPM combines the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)-algorithm for Outlier Detection(OD)and the Random Forest(RF)classification algorithm for removing the outlier SD and providing Fault Detection(FD)when the PD isn’t working.The suggested work is assessed and tested under various fault circumstances that happened in PSs.The simulation outcome proves that the proposed model is effective in monitoring the smooth functioning of the PS.Also,the suggested HPM has a higher Fault Prediction(FP)accuracy.This means that faults can be found earlier,early warning signals can be sent,and the power supply can be turned off quickly to ensure electrical safety.A powerful RTM and event warning system can also be built into the system before faults happen.
基金This project was funded by the Deanship of Scientific Research(DSR),King Abdulaziz University,Jeddah,under Grant No.(D-15-611-1443).
文摘Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise.Moreover,it is widely utilizing for preventing injuries of athletes during a practice session and in few cases,it leads to muscle fatigue.At present,emerging technology like the internet of things(IoT)and sensors is empowering to monitor and visualize the physical data from any remote location through internet connectivity.In this study,an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram(sEMG)sensor.Normally,the EMG signal is utilized to display muscle activity.Arduino controller,Wi-Fi module,and EMG sensor are utilized in developing the wearable device.The Time-frequency domain spectrum technique is employed for classifying the threemuscle fatigue conditions including meanRMS,mean frequency,etc.A real-time experiment is realized on six different individuals with developed wearable devices and the average RMS value assists to determine the average threshold of recorded data.The threshold level is analyzed by calculating the mean RMS value and concluded three fatigue conditions as>2V:Extensive);1–2V:Moderate,and<1V:relaxed.The warning alarm system was designed in LabVIEW with three color LEDs to indicate the different states of muscle fatigue.Moreover,the device is interfaced with the cloud through the internet provided with a Wi-Fi module embedded in wearable devices.The data available in the cloud server can be utilized for forecasting the frequency of an individual to muscle fatigue.
基金Supported by the National Natural Science Foundation of China(61101088)the Opening Project of Key Lab of Information Network Security of Ministry of Public Security(C13607)
文摘This paper analyzes the efficiency and security of bi- linear-map-based schemes and brings about an AAA based publicly auditable scheme for cloud computing, which is much more efficient. In this scheme, a trust model including four entities is designed to provide both integrity and confidentiality protection. The proposed scheme can be proved to achieve the security goals that no cheating cloud server can pass the auditing without storing users＇ data intact. The efficiency of the proposal is evaluated by analyzing the fulfillment of the design goals, including the computation cost, communication cost and storage cost of our scheme. This light weight publicly auditable Proof-of-storage scheme achieves security goals perfectly, and has an excellent efficiency performance superior to the current bilinear-map-based publicly auditable Proof-of-storage scheme.
文摘With the increasing importance of cloud services worldwide, the cloud infrastructure and platform management has become critical for cloud service providers. In this paper, a novel architecture of intelligent server management framework is proposed. In this framework, the communication layer is based on the Extensible Messaging and Presence Protocol (XMPP), which was developed for instant messaging and has been proven to be highly mature and suitable for mobile and large scalable deployment due to its extensibility and efficiency. The proposed architecture can simplify server management and increase flexibility and scalability when managing hundreds of thousands of servers in the cloud era.
文摘This paper considers the collaborative resource allocation problem over a hybrid cloud center and edge server network, an emerging infrastructure for efficient Internet services. The cloud center acts as a pool of inexhaustible computation and storage powers. The edge servers often have limited computation and storage powers but are able to provide quick responses to service requests from end users. Upon receiving service requests, edge servers assign them to themselves, their neighboring edge servers, as well as the cloud center, aiming at minimizing the overall network cost. This paper first establishes an optimization model for this problem. Second, in light of the separable structure of the optimization model, we utilize the alternating direction method of multipliers （ADMM） to develop a fully collaborative resource allocation algorithm. The edge servers and the cloud center autonomously collaborate to compute their local optimization variables and prices of network resources, and reach an optimal solution. Numerical experiments demonstrate the effectiveness of the hybrid network infrastructure as well as the proposed algorithm.
