Due to the security and scalability features of hybrid cloud architecture,it can bettermeet the diverse requirements of users for cloud services.And a reasonable resource allocation solution is the key to adequately u...Due to the security and scalability features of hybrid cloud architecture,it can bettermeet the diverse requirements of users for cloud services.And a reasonable resource allocation solution is the key to adequately utilize the hybrid cloud.However,most previous studies have not comprehensively optimized the performance of hybrid cloud task scheduling,even ignoring the conflicts between its security privacy features and other requirements.Based on the above problems,a many-objective hybrid cloud task scheduling optimization model(HCTSO)is constructed combining risk rate,resource utilization,total cost,and task completion time.Meanwhile,an opposition-based learning knee point-driven many-objective evolutionary algorithm(OBL-KnEA)is proposed to improve the performance of model solving.The algorithm uses opposition-based learning to generate initial populations for faster convergence.Furthermore,a perturbation-based multipoint crossover operator and a dynamic range mutation operator are designed to extend the search range.By comparing the experiments with other excellent algorithms on HCTSO,OBL-KnEA achieves excellent results in terms of evaluation metrics,initial populations,and model optimization effects.展开更多
Internet of things(IoT)and cloud computing(CC)becomes widespread in different application domains such as business,e-commerce,healthcare,etc.The recent developments of IoT technology have led to an increase in large a...Internet of things(IoT)and cloud computing(CC)becomes widespread in different application domains such as business,e-commerce,healthcare,etc.The recent developments of IoT technology have led to an increase in large amounts of data from various sources.In IoT enabled cloud environment,load scheduling remains a challenging process which is applied for ensuring network stability with maximum resource utilization.The load scheduling problem was regarded as an optimization problem that is solved by metaheuristics.In this view,this study develops a new Circle Chaotic Chameleon Swarm Optimization based Load Scheduling(C3SOA-LS)technique for IoT enabled cloud environment.The proposed C3SOA-LS technique intends to effectually schedule the tasks and balance the load uniformly in such a way that maximum resource utilization can be accomplished.Besides,the presented C3SOA-LS model involves the design of circle chaotic mapping(CCM)with the traditional chameleon swarm optimization(CSO)algorithm for improving the exploration process,shows the novelty of the work.The proposed C3SOA-LS model computes an objective with the minimization of energy consumption and makespan.The experimental outcome implied that the C3SOA-LS model has showcased improved performance and uniformly balances the load over other approaches.展开更多
With the increasing number of resources provided by cloud environments, identifying which types of resources should be rent when deploying an application is often a difficult and error-prone process. Currently, most c...With the increasing number of resources provided by cloud environments, identifying which types of resources should be rent when deploying an application is often a difficult and error-prone process. Currently, most cloud environments offer a wide range of configurable resources, which can be combined in many different ways. Finding an appropriate configuration under cost constraints while meeting requirements is still a challenge. In this paper, software product line engineering is introduced to describe cloud environments, and configurable resources are abstracted as features with attributes. Then, a Self-Tuning Particle Swarm Optimization approach(called STPSO) is proposed to configure the cloud environment. STPSO can automatically adjust the arbitrary configuration to a valid configuration. To evaluate the performance of the proposed approach, we conduct a series of comprehensive experiments. The empirical experiment shows that our approach reduces time and provides a reliable way to find a correct and suitable cloud configuration when dealing with a significant number of resources.展开更多
The Cloud Computing Environment(CCE)developed for using the dynamic cloud is the ability of software and services likely to grow with any business.It has transformed the methodology for storing the enterprise data,acc...The Cloud Computing Environment(CCE)developed for using the dynamic cloud is the ability of software and services likely to grow with any business.It has transformed the methodology for storing the enterprise data,accessing the data,and Data Sharing(DS).Big data frame a constant way of uploading and sharing the cloud data in a hierarchical architecture with different kinds of separate privileges to access the data.With the requirement of vast volumes of storage area in the CCEs,capturing a secured data access framework is an important issue.This paper proposes an Improved Secure Identification-based Multilevel Structure of Data Sharing(ISIMSDS)to hold the DS of big data in CCEs.The complex file partitioning technique is proposed to verify the access privilege context for sharing data in complex CCEs.An access control Encryption Method(EM)is used to improve the encryption.The Complexity is measured to increase the authentication standard.The active attack is protected using this ISIMSDS methodology.Our proposed ISIMSDS method assists in diminishing the Complexity whenever the user’s population is increasing rapidly.The security analysis proves that the proposed ISIMSDS methodology is more secure against the chosen-PlainText(PT)attack and provides more efficient computation and storage space than the related methods.The performance of the proposed ISIMSDS methodology provides more efficiency in communication costs such as encryption,decryption,and retrieval of the data.展开更多
Reversible data hiding techniques are capable of reconstructing the original cover image from stego-images. Recently, many researchers have focused on reversible data hiding to protect intellectual property rights. In...Reversible data hiding techniques are capable of reconstructing the original cover image from stego-images. Recently, many researchers have focused on reversible data hiding to protect intellectual property rights. In this paper, we combine reversible data hiding with the chaotic Henon map as an encryption technique to achieve an acceptable level of confidentiality in cloud computing environments. And, Haar digital wavelet transformation （HDWT） is also applied to convert an image from a spatial domain into a frequency domain. And then the decimal of coefficients and integer of high frequency band are modified for hiding secret bits. Finally, the modified coefficients are inversely transformed to stego-images.展开更多
Typhoon-induced heavy rains are mostly studied from the viewpoint of upper-level westerly troughs. It is worthwhile to probe into a case where the rain is caused by tropical cyclone system, which is much heavier. Duri...Typhoon-induced heavy rains are mostly studied from the viewpoint of upper-level westerly troughs. It is worthwhile to probe into a case where the rain is caused by tropical cyclone system, which is much heavier. During August 3 ~ 5, 1996, an unusually heavy rainstorm happened in the southwest of Hebei province. It was caused by 3 mesoscale convective cloud clusters on the periphery of a tropical cyclone other than the direct effects of a westerly trough. Generating in a weak baroclinic environment that is unstable with high energy, the cloud clusters were triggered off for development by unstable ageostrophic gravity waves in the low-level southeast jet stream on the periphery of the typhoon. There was a vertical circulation cell with horizontal scale close to 1000 km between the rainstorm area and westerly trough in northeast China. As shown in a computation of the Q vector of frontogenesis function, the circulation cell forms a mechanism of transforming energy between the area of interest and the westerly trough system farther away in northeast China. Study of water vapor chart indicates that high-latitude troughs in the northeast portion of the rain migrate to the southeast to enhance anti-cyclonic divergence in upper-level convection over the area of heavy rain and cause rain clusters, short-lived otherwise, to develop vigorously. It is acting as an amplifier in this case of unusually strong process of rain.展开更多
The COVID-19 pandemic has affected the educational systems worldwide,leading to the near-total closures of schools,universities,and colleges.Universities need to adapt to changes to face this crisis without negatively...The COVID-19 pandemic has affected the educational systems worldwide,leading to the near-total closures of schools,universities,and colleges.Universities need to adapt to changes to face this crisis without negatively affecting students’performance.Accordingly,the purpose of this study is to identify and help solve to critical challenges and factors that influence the e-learning system for Computer Maintenance courses during the COVID-19 pandemic.The paper examines the effect of a hybrid modeling approach that uses Cloud Computing Services(CCS)and Virtual Reality(VR)in a Virtual Cloud Learning Environment(VCLE)system.The VCLE system provides students with various utilities and educational services such as presentation slides/text,data sharing,assignments,quizzes/tests,and chatrooms.In addition,learning through VR enables the students to simulate physical presence,and they respond well to VR environments that are closer to reality as they feel that they are an integral part of the environment.Also,the research presents a rubric assessment that the students can use to reflect on the skills they used during the course.The research findings offer useful suggestions for enabling students to become acquainted with the proposed system’s usage,especially during theCOVID-19 pandemic,and for improving student achievementmore than the traditional methods of learning.展开更多
Infrastructure as a Service(IaaS)provides logical separation between data,network,applications and machines from the physical constrains of real machines.IaaS is one of the basis of cloud virtualization.Recently,secur...Infrastructure as a Service(IaaS)provides logical separation between data,network,applications and machines from the physical constrains of real machines.IaaS is one of the basis of cloud virtualization.Recently,security issues are also gradually emerging with virtualization of cloud computing.Different security aspects of cloud virtualization will be explored in this research paper,security recognizing potential threats or attacks that exploit these vulnerabilities,and what security measures are used to alleviate such threats.In addition,a dis-cussion of general security requirements and the existing security schemes is also provided.As shown in this paper,different components of virtualization environ-ment are targets to various attacks that in turn leads to security issues compromis-ing the whole cloud infrastructure.In this paper an overview of various cloud security aspects is also provided.Different attack scenarios of virtualization envir-onments and security solutions to cater these attacks have been discussed in the paper.We then proceed to discuss API security concerns,data security,hijacking of user account and other security concerns.The aforementioned discussions can be used in the future to propose assessment criteria,which could be useful in ana-lyzing the efficiency of security solutions of virtualization environment in the face of various virtual environment attacks.展开更多
A subject who wears a suitable robotic device will be able to walk in complex environments with the aid of environmental recognition schemes that provide reliable prior information of the human motion intent.Researche...A subject who wears a suitable robotic device will be able to walk in complex environments with the aid of environmental recognition schemes that provide reliable prior information of the human motion intent.Researchers have utilized 1 D laser signals and 2 D depth images to classify environments,but those approaches can face the problems of self-occlusion.In comparison,3 D point cloud is more appropriate for depicting the environments.This paper proposes a directional PointNet to directly classify the 3 D point cloud.First,an inertial measurement unit(IMU)is used to offset the orientation of point cloud.Then the directional PointNet can accurately classify the daily commuted terrains,including level ground,climbing up stairways,and walking down stairs.A classification accuracy of 98%has been achieved in tests.Moreover,the directional PointNet is more efficient than the previously used PointNet because the T-net,which is utilized to estimate the transformation of the point cloud,is not used in the present approach,and the length of the global feature is optimized.The experimental results demonstrate that the directional PointNet can classify the environments in robust and efficient manner.展开更多
Firms need cloud computing adoption for strategic and competitive goals, generating business value, and at last gaining competitive advantage. This study reviews the literature regarding cloud computing and IT governa...Firms need cloud computing adoption for strategic and competitive goals, generating business value, and at last gaining competitive advantage. This study reviews the literature regarding cloud computing and IT governance, and presents a research model along with its hypotheses formulation to examine the factors impacting cloud computing perceived importance in several Arab firms, specifically Jordan, Saudi Arabia and United Arab Emirates by using the integration of Technology Acceptance Model (TAM) model and Technology-Organizational-Environmental (TOE) framework as adapted from [1]. 329 returned surveys from top, middle-level IT managers, and IT employees from the operational level of the studied firms were analyzed using the structural equation modeling technique. The study found relative advantage, compatibility, complexity, organizational readiness, top management commitment, and training and education as important variables for impacting cloud computing adoption using perceived ease of use and perceived usefulness as mediating variables. The model explained 61%, 63%, and 74% of cloud computing adoption for perceived usefulness, perceived ease of use and perceived importance respectively.展开更多
基金supported by National Natural Science Foundation of China(Grant No.61806138)the Central Government Guides Local Science and Technology Development Funds(Grant No.YDZJSX2021A038)+2 种基金Key RD Program of Shanxi Province(International Cooperation)under Grant No.201903D421048Outstanding Innovation Project for Graduate Students of Taiyuan University of Science and Technology(Project No.XCX211004)China University Industry-University-Research Collaborative Innovation Fund(Future Network Innovation Research and Application Project)(Grant 2021FNA04014).
文摘Due to the security and scalability features of hybrid cloud architecture,it can bettermeet the diverse requirements of users for cloud services.And a reasonable resource allocation solution is the key to adequately utilize the hybrid cloud.However,most previous studies have not comprehensively optimized the performance of hybrid cloud task scheduling,even ignoring the conflicts between its security privacy features and other requirements.Based on the above problems,a many-objective hybrid cloud task scheduling optimization model(HCTSO)is constructed combining risk rate,resource utilization,total cost,and task completion time.Meanwhile,an opposition-based learning knee point-driven many-objective evolutionary algorithm(OBL-KnEA)is proposed to improve the performance of model solving.The algorithm uses opposition-based learning to generate initial populations for faster convergence.Furthermore,a perturbation-based multipoint crossover operator and a dynamic range mutation operator are designed to extend the search range.By comparing the experiments with other excellent algorithms on HCTSO,OBL-KnEA achieves excellent results in terms of evaluation metrics,initial populations,and model optimization effects.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under Grant Number(RGP 1/322/42)Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R136)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4340237DSR09).
文摘Internet of things(IoT)and cloud computing(CC)becomes widespread in different application domains such as business,e-commerce,healthcare,etc.The recent developments of IoT technology have led to an increase in large amounts of data from various sources.In IoT enabled cloud environment,load scheduling remains a challenging process which is applied for ensuring network stability with maximum resource utilization.The load scheduling problem was regarded as an optimization problem that is solved by metaheuristics.In this view,this study develops a new Circle Chaotic Chameleon Swarm Optimization based Load Scheduling(C3SOA-LS)technique for IoT enabled cloud environment.The proposed C3SOA-LS technique intends to effectually schedule the tasks and balance the load uniformly in such a way that maximum resource utilization can be accomplished.Besides,the presented C3SOA-LS model involves the design of circle chaotic mapping(CCM)with the traditional chameleon swarm optimization(CSO)algorithm for improving the exploration process,shows the novelty of the work.The proposed C3SOA-LS model computes an objective with the minimization of energy consumption and makespan.The experimental outcome implied that the C3SOA-LS model has showcased improved performance and uniformly balances the load over other approaches.
基金supported by the Foundation for Outstanding Young Scientist in Shandong Province (No. BS2014DX021)the Fundamental Research Funds for the Central Universities (No. 14CX02136A)the National Natural Science Foundation of China (Grant No. 61402533)
文摘With the increasing number of resources provided by cloud environments, identifying which types of resources should be rent when deploying an application is often a difficult and error-prone process. Currently, most cloud environments offer a wide range of configurable resources, which can be combined in many different ways. Finding an appropriate configuration under cost constraints while meeting requirements is still a challenge. In this paper, software product line engineering is introduced to describe cloud environments, and configurable resources are abstracted as features with attributes. Then, a Self-Tuning Particle Swarm Optimization approach(called STPSO) is proposed to configure the cloud environment. STPSO can automatically adjust the arbitrary configuration to a valid configuration. To evaluate the performance of the proposed approach, we conduct a series of comprehensive experiments. The empirical experiment shows that our approach reduces time and provides a reliable way to find a correct and suitable cloud configuration when dealing with a significant number of resources.
文摘The Cloud Computing Environment(CCE)developed for using the dynamic cloud is the ability of software and services likely to grow with any business.It has transformed the methodology for storing the enterprise data,accessing the data,and Data Sharing(DS).Big data frame a constant way of uploading and sharing the cloud data in a hierarchical architecture with different kinds of separate privileges to access the data.With the requirement of vast volumes of storage area in the CCEs,capturing a secured data access framework is an important issue.This paper proposes an Improved Secure Identification-based Multilevel Structure of Data Sharing(ISIMSDS)to hold the DS of big data in CCEs.The complex file partitioning technique is proposed to verify the access privilege context for sharing data in complex CCEs.An access control Encryption Method(EM)is used to improve the encryption.The Complexity is measured to increase the authentication standard.The active attack is protected using this ISIMSDS methodology.Our proposed ISIMSDS method assists in diminishing the Complexity whenever the user’s population is increasing rapidly.The security analysis proves that the proposed ISIMSDS methodology is more secure against the chosen-PlainText(PT)attack and provides more efficient computation and storage space than the related methods.The performance of the proposed ISIMSDS methodology provides more efficiency in communication costs such as encryption,decryption,and retrieval of the data.
文摘Reversible data hiding techniques are capable of reconstructing the original cover image from stego-images. Recently, many researchers have focused on reversible data hiding to protect intellectual property rights. In this paper, we combine reversible data hiding with the chaotic Henon map as an encryption technique to achieve an acceptable level of confidentiality in cloud computing environments. And, Haar digital wavelet transformation （HDWT） is also applied to convert an image from a spatial domain into a frequency domain. And then the decimal of coefficients and integer of high frequency band are modified for hiding secret bits. Finally, the modified coefficients are inversely transformed to stego-images.
文摘Typhoon-induced heavy rains are mostly studied from the viewpoint of upper-level westerly troughs. It is worthwhile to probe into a case where the rain is caused by tropical cyclone system, which is much heavier. During August 3 ~ 5, 1996, an unusually heavy rainstorm happened in the southwest of Hebei province. It was caused by 3 mesoscale convective cloud clusters on the periphery of a tropical cyclone other than the direct effects of a westerly trough. Generating in a weak baroclinic environment that is unstable with high energy, the cloud clusters were triggered off for development by unstable ageostrophic gravity waves in the low-level southeast jet stream on the periphery of the typhoon. There was a vertical circulation cell with horizontal scale close to 1000 km between the rainstorm area and westerly trough in northeast China. As shown in a computation of the Q vector of frontogenesis function, the circulation cell forms a mechanism of transforming energy between the area of interest and the westerly trough system farther away in northeast China. Study of water vapor chart indicates that high-latitude troughs in the northeast portion of the rain migrate to the southeast to enhance anti-cyclonic divergence in upper-level convection over the area of heavy rain and cause rain clusters, short-lived otherwise, to develop vigorously. It is acting as an amplifier in this case of unusually strong process of rain.
文摘The COVID-19 pandemic has affected the educational systems worldwide,leading to the near-total closures of schools,universities,and colleges.Universities need to adapt to changes to face this crisis without negatively affecting students’performance.Accordingly,the purpose of this study is to identify and help solve to critical challenges and factors that influence the e-learning system for Computer Maintenance courses during the COVID-19 pandemic.The paper examines the effect of a hybrid modeling approach that uses Cloud Computing Services(CCS)and Virtual Reality(VR)in a Virtual Cloud Learning Environment(VCLE)system.The VCLE system provides students with various utilities and educational services such as presentation slides/text,data sharing,assignments,quizzes/tests,and chatrooms.In addition,learning through VR enables the students to simulate physical presence,and they respond well to VR environments that are closer to reality as they feel that they are an integral part of the environment.Also,the research presents a rubric assessment that the students can use to reflect on the skills they used during the course.The research findings offer useful suggestions for enabling students to become acquainted with the proposed system’s usage,especially during theCOVID-19 pandemic,and for improving student achievementmore than the traditional methods of learning.
文摘Infrastructure as a Service(IaaS)provides logical separation between data,network,applications and machines from the physical constrains of real machines.IaaS is one of the basis of cloud virtualization.Recently,security issues are also gradually emerging with virtualization of cloud computing.Different security aspects of cloud virtualization will be explored in this research paper,security recognizing potential threats or attacks that exploit these vulnerabilities,and what security measures are used to alleviate such threats.In addition,a dis-cussion of general security requirements and the existing security schemes is also provided.As shown in this paper,different components of virtualization environ-ment are targets to various attacks that in turn leads to security issues compromis-ing the whole cloud infrastructure.In this paper an overview of various cloud security aspects is also provided.Different attack scenarios of virtualization envir-onments and security solutions to cater these attacks have been discussed in the paper.We then proceed to discuss API security concerns,data security,hijacking of user account and other security concerns.The aforementioned discussions can be used in the future to propose assessment criteria,which could be useful in ana-lyzing the efficiency of security solutions of virtualization environment in the face of various virtual environment attacks.
文摘A subject who wears a suitable robotic device will be able to walk in complex environments with the aid of environmental recognition schemes that provide reliable prior information of the human motion intent.Researchers have utilized 1 D laser signals and 2 D depth images to classify environments,but those approaches can face the problems of self-occlusion.In comparison,3 D point cloud is more appropriate for depicting the environments.This paper proposes a directional PointNet to directly classify the 3 D point cloud.First,an inertial measurement unit(IMU)is used to offset the orientation of point cloud.Then the directional PointNet can accurately classify the daily commuted terrains,including level ground,climbing up stairways,and walking down stairs.A classification accuracy of 98%has been achieved in tests.Moreover,the directional PointNet is more efficient than the previously used PointNet because the T-net,which is utilized to estimate the transformation of the point cloud,is not used in the present approach,and the length of the global feature is optimized.The experimental results demonstrate that the directional PointNet can classify the environments in robust and efficient manner.
文摘Firms need cloud computing adoption for strategic and competitive goals, generating business value, and at last gaining competitive advantage. This study reviews the literature regarding cloud computing and IT governance, and presents a research model along with its hypotheses formulation to examine the factors impacting cloud computing perceived importance in several Arab firms, specifically Jordan, Saudi Arabia and United Arab Emirates by using the integration of Technology Acceptance Model (TAM) model and Technology-Organizational-Environmental (TOE) framework as adapted from [1]. 329 returned surveys from top, middle-level IT managers, and IT employees from the operational level of the studied firms were analyzed using the structural equation modeling technique. The study found relative advantage, compatibility, complexity, organizational readiness, top management commitment, and training and education as important variables for impacting cloud computing adoption using perceived ease of use and perceived usefulness as mediating variables. The model explained 61%, 63%, and 74% of cloud computing adoption for perceived usefulness, perceived ease of use and perceived importance respectively.
