With the development of medical sensors and IoT, personalized service assisted elder and patient living is a critical service in IoT-based healthcare application. However, the scale and complexity of personalized serv...With the development of medical sensors and IoT, personalized service assisted elder and patient living is a critical service in IoT-based healthcare application. However, the scale and complexity of personalized service is increasing because of ubiquitous deployment of various kinds of medical sensors, which cause response time increase and resource waste. Therefore, leveraging the advantage of complex event processing(CEP) in data stream processing, we propose a hierarchical fog-cloud computing CEP architecture for personalized service to accelerate response time and reduce resource waste. Firstly, we introduce the proposed architecture, which includes sensor layer, fog layer and cloud layer. Secondly, we propose a series of optimizations for the architecture, there are a partitioning and clustering approach and a communication and parallel processing policy to optimize the fog and cloud computing. Finally, we implement a prototype system based on the architecture named Fog Cep Care. Experimental result shows that Fog Cep Care is superior to the traditional IoT-based healthcare application.展开更多
This paper proposes an architecture model to support enhanced system performance in large-scale pervasive computing environments. The muitiformity of device （or peer ） services and network types in such environment ...This paper proposes an architecture model to support enhanced system performance in large-scale pervasive computing environments. The muitiformity of device （or peer ） services and network types in such environment is apt to result in notable service isomorphs. And moreover, as the environment cannot assure the stability of network communication and device services, the situation gets worse. Therefore, it becomes urgent to simplify user operations and let them take full and highly efficient advantage of the environments. Super-Service-Odented Architecture （SSOA） is an Serrice-Otiented Architecture （SOA）-based architecture for service management and organization in peryasive environments. With combining one kind of isomorphic services into a super service, SSOA provides better scalability and quick, convenient service invocations. Also, the complexity and instability of services, and network types are transparent, and system performance is highly promoted under the architecture.展开更多
Based on the features of marine environmental data and processing requirements, a cloud computing archi- tecture of marine environment information is proposed, which provides a new cloud technology framework for the i...Based on the features of marine environmental data and processing requirements, a cloud computing archi- tecture of marine environment information is proposed, which provides a new cloud technology framework for the integration and sharing of marine environmental information resources. A physical layer, software platform layer and an application layer are illustrated systematically, at the same time, a corresponding solu- tions for many difficult technical problems such as parallel query processing of multi-dimensional, spatio- temporal information, data slice storage, software service flow customization, analysis, reorganization and so on. A prototype system is developed and many different data-size experiments and a comparative analy- sis are done based on it. The experiment results show that the cloud platform based on this framework can achieve high performance and scalability when dealing with large-scale marine data.展开更多
Security is a key problem for the development of Cloud Computing. A common service security architecture is a basic abstract to support security research work. The authorization ability in the service security faces m...Security is a key problem for the development of Cloud Computing. A common service security architecture is a basic abstract to support security research work. The authorization ability in the service security faces more complex and variable users and environment. Based on the multidimensional views, the service security architecture is described on three dimensions of service security requirement integrating security attributes and service layers. An attribute-based dynamic access control model is presented to detail the relationships among subjects, objects, roles, attributes, context and extra factors further. The model uses dynamic control policies to support the multiple roles and flexible authority. At last, access control and policies execution mechanism were studied as the implementation suggestion.展开更多
After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtuali...After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.展开更多
This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of conte...This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of context-aware service during preparation,organization and delivery,as well as the resulting changes in service acceptance of consumers.Because of these changes,the context-aware service modes in the cloud computing environment change are intelligent,immersive,highly interactive,and real-time.According to active and responded service,and authorization and non-authorized service,the paper drew a case diagram of context-aware service in Unified Modeling Language(UML) and established four categories of context-aware service modes.展开更多
In the current cloud-based Internet-of-Things （IoT） model, smart devices （such as sensors, smartphones） exchange information through the Internet to cooperate and provide services to users, which could be citizens...In the current cloud-based Internet-of-Things （IoT） model, smart devices （such as sensors, smartphones） exchange information through the Internet to cooperate and provide services to users, which could be citizens, smart home systems, and industrial applications.展开更多
The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applic...The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applications.Most existing studies focusing on the issue of task offloading in ICVs assume that the MEC server can directly complete computation tasks without considering the necessity of service caching.However,this is unrealistic in practice because a large number of tasks require the use of corresponding third-party libraries and databases,that is,service caching.Therefore,we investigate the delay optimization in an MEC-enabled ICVs system with multiple mobile vehicles,resource-limited base stations(BSs),and one cloud server.We aim to determine the optimal service caching and task offloading decisions to minimize the overall system delay using mixed-integer nonlinear programming.To address this problem,we first convert it into a quadratically constrained quadratic program and then propose an efficient semidefinite relaxation-based joint service caching and task offloading(JSCTO)algorithm to obtain the service caching and task offloading decisions.In the simulations,we validate the efficiency of our proposed method by setting different numbers of vehicles and the storage capacity of BSs.The results show that our proposed JSCTO algorithm can significantly decrease the total delay of all offloaded tasks compared with the cloud processing only scheme.展开更多
With the growing amounts of multi-micro grids,electric vehicles,smart home,smart cities connected to the Power Distribution Internet of Things(PD-IoT)system,greater computing resource and communication bandwidth are r...With the growing amounts of multi-micro grids,electric vehicles,smart home,smart cities connected to the Power Distribution Internet of Things(PD-IoT)system,greater computing resource and communication bandwidth are required for power distribution.It probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence.This paper presents a service scheduling method based on edge computing to balance the business load of PD-IoT.The architecture,components and functional requirements of the PD-IoT with edge computing platform are proposed.Then,the structure of the service scheduling system is presented.Further,a novel load balancing strategy and ant colony algorithm are investigated in the service scheduling method.The validity of the method is evaluated by simulation tests.Results indicate that the mean load balancing ratio is reduced by 99.16%and the optimized offloading links can be acquired within 1.8 iterations.Computing load of the nodes in edge computing platform can be effectively balanced through the service scheduling.展开更多
Cloud computing is becoming a hot topic of the information industry in recent years. Many companies provide the cloud services, such as Google Apps and Apple multimedia services. In general, by applying the virtulizat...Cloud computing is becoming a hot topic of the information industry in recent years. Many companies provide the cloud services, such as Google Apps and Apple multimedia services. In general, by applying the virtulization technologies, the data center is built for cloud computing to provide users with the eomputing and storage resources, as well as the software environment. Thus, the quality of service （QoS） must be considered to satisfy users＇ requirements. This paper proposes a high efficiency scheduling scheme for supporting cloud computing. The virtual machine migration technique has been applied to the proposed scheduling scheme for improving the resources utilization and satisfying the QoS requirement of users. The experimental results show that in addition to satisfying the QoS requirement of users, the proposed scheme can improve the resources utilization effectively.展开更多
Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industr...Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industry adoption and migration of traditional computing services to the cloud,one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies.This work proposes a Data Security Framework for cloud computing services(CCS)that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS.This framework is developed by means of a methodology based on a heuristic theory that incorporates knowledge generated by existing works as well as the experience of their implementation.The paper presents the design details of the framework,which consists of three stages:identification of data security requirements,management of data security risks and evaluation of data security performance in CCS.展开更多
Mobile edge computing(MEC) is a cloud server running at the edge of a mobile network, which can effectively reduce network communication delay. However, due to the numerous edge servers and devices in the MEC, there m...Mobile edge computing(MEC) is a cloud server running at the edge of a mobile network, which can effectively reduce network communication delay. However, due to the numerous edge servers and devices in the MEC, there may be multiple servers and devices that can provide services to the same user simultaneously. This paper proposes a userside adaptive user service deployment algorithm ASD(Adaptive Service Deployment) based on reinforcement learning algorithms. Without relying on complex system information, it can master only a few tasks and users. In the case of attributes, perform effective service deployment decisions, analyze and redefine the key parameters of existing algorithms, and dynamically adjust strategies according to task types and available node types to optimize user experience delay. Experiments show that the ASD algorithm can implement user-side decision-making for service deployment. While effectively improving parameter settings in the traditional Multi-Armed Bandit algorithm,it can reduce user-perceived delay and enhance service quality compared with other strategies.展开更多
Cloud computing is one of the main issues of interest to the scientific community of the spatial data. A cloud is referred to computing infrastructure for a representation of network. From the perspective of providers...Cloud computing is one of the main issues of interest to the scientific community of the spatial data. A cloud is referred to computing infrastructure for a representation of network. From the perspective of providers, the main characteristics of cloud computing is being dynamic, high power in computing and storage. Also cloud computing is a cost benefit and effective way for representation of web-based spatial data and complex analysis. Furthermore, cloud computing is a way to facilitate distributed computing and store different data. One of the main features of cloud computing is ability in powerful computing and dynamic storage with an affordable expense and secure web. In this paper we further investigate the methodologies, services, issues and deployed techniques also, about situation of cloud computing in the past, present and future is probed and some issues concerning the security is expressed. Undoubtedly cloud computing is vital for spatial data infrastructure and consequently the cloud computing is able to expand the interactions for spatial data infrastructure in the future.展开更多
Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy....Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.展开更多
Mobility and resource-limitedness pose challenging issues to service configuration for quality of service (QoS) management in ubiquitous computing environments. Previous configuration approaches, such as static resour...Mobility and resource-limitedness pose challenging issues to service configuration for quality of service (QoS) management in ubiquitous computing environments. Previous configuration approaches, such as static resource reservation, dynamic resource allocation and single service composition are not valid in the environments. In this study, we present an adaptive service configuration approach. Firstly, we reduce the dynamic configuration process to a control model which aims to achieve the variation of critical QoS on minimal level with less resource cost. Secondly, to deal with different QoS variations, we design two configuration strategies—service chain reconfiguration and QoS parameter adjustment—and implement them based on fuzzy logic control theory. Finally, a configuration algorithm is developed to flexibly employ the two configuration strategies in tune with the error of critical QoS in configuration process. The results of simulation experiments suggest that our approach outper- forms existing configuration approaches in both QoS improvement and resource utilization.展开更多
Cloud computing is high technology, which fulfills needs of common as well as enterprise level to meet their information and communication technology requirements and so on. Cloud computing extends existing informatio...Cloud computing is high technology, which fulfills needs of common as well as enterprise level to meet their information and communication technology requirements and so on. Cloud computing extends existing information technology capabilities and requirements. Many technologies are being merged with cloud computing, same as that orchestrations can boost cloud service provisioning process. The usage of orchestrations can play vital role to provision cloud services. Cloud service providers can create scalable cloud services at low cost by organizing cloud infrastructure by using cloud orchestrations. Dynamic orchestration flows can generate required cloud computing services to meet service level agreements and quality of services. There is a need to understand issues and barriers involved to integrate cloud orchestrations with cloud service provisioning process. There is also need to understand business related problems bordering cloud computing technology. There is much capacity to do targeted research work for cloud orchestrations and its integration with service level agreements as well as with SLI (service level integration) layer. In this article we have elaborated detailed analysis and identified a number of issues that will affect the cloud service users as well as cloud service providers and cloud service provisioning system. We are defining an approach to orchestrate cloud infrastructure by using orchestration flows, to generate cloud services in order to meet service level agreements and quality of standard.展开更多
Enhancements in technology always follow Consumer requirements. Consumer requires best of service with least possible mismatch and on time. Numerous applications available today are based on Web Services and Cloud Com...Enhancements in technology always follow Consumer requirements. Consumer requires best of service with least possible mismatch and on time. Numerous applications available today are based on Web Services and Cloud Computing. Recently, there exist many Web Services with similar functional characteristics. Choosing “a-right” Service from group of similar Web Service is a complicated task for Service Consumer. In that case, Service Consumer can discover the required Web Service using non functional attributes of the Web Services such as QoS. Proposed layered architecture and Web Service-Cloud, i.e. WS-Cloud computing Framework synthesizes the non functional attributes that includes reliability, availability, response time, latency etc. The Service Consumer is projected to provide the QoS requirements as part of Service discovery query. This framework will discover and filter the Web Services form the cloud and rank them according to Service Consumer preferences to facilitate Service on time.展开更多
Big Data applications are pervading more and more aspects of our life, encompassing commercial and scientific uses at increasing rates as we move towards exascale analytics. Examples of Big Data applications include s...Big Data applications are pervading more and more aspects of our life, encompassing commercial and scientific uses at increasing rates as we move towards exascale analytics. Examples of Big Data applications include storing and accessing user data in commercial clouds, mining of social data, and analysis of large-scale simulations and experiments such as the Large Hadron Collider. An increasing number of such data—intensive applications and services are relying on clouds in order to process and manage the enormous amounts of data required for continuous operation. It can be difficult to decide which of the many options for cloud processing is suitable for a given application;the aim of this paper is therefore to provide an interested user with an overview of the most important concepts of cloud computing as it relates to processing of Big Data.展开更多
基金supported in part by the National High-tech R&D Program of China(863 Program) under Grant No. 2013AA102301Shandong Provincial Natural Science Foundation(No. ZR2017MF050)
文摘With the development of medical sensors and IoT, personalized service assisted elder and patient living is a critical service in IoT-based healthcare application. However, the scale and complexity of personalized service is increasing because of ubiquitous deployment of various kinds of medical sensors, which cause response time increase and resource waste. Therefore, leveraging the advantage of complex event processing(CEP) in data stream processing, we propose a hierarchical fog-cloud computing CEP architecture for personalized service to accelerate response time and reduce resource waste. Firstly, we introduce the proposed architecture, which includes sensor layer, fog layer and cloud layer. Secondly, we propose a series of optimizations for the architecture, there are a partitioning and clustering approach and a communication and parallel processing policy to optimize the fog and cloud computing. Finally, we implement a prototype system based on the architecture named Fog Cep Care. Experimental result shows that Fog Cep Care is superior to the traditional IoT-based healthcare application.
文摘This paper proposes an architecture model to support enhanced system performance in large-scale pervasive computing environments. The muitiformity of device （or peer ） services and network types in such environment is apt to result in notable service isomorphs. And moreover, as the environment cannot assure the stability of network communication and device services, the situation gets worse. Therefore, it becomes urgent to simplify user operations and let them take full and highly efficient advantage of the environments. Super-Service-Odented Architecture （SSOA） is an Serrice-Otiented Architecture （SOA）-based architecture for service management and organization in peryasive environments. With combining one kind of isomorphic services into a super service, SSOA provides better scalability and quick, convenient service invocations. Also, the complexity and instability of services, and network types are transparent, and system performance is highly promoted under the architecture.
基金the Ocean Public Welfare Scientific Research Project of State Oceanic Administration of China under contract No.201105033
文摘Based on the features of marine environmental data and processing requirements, a cloud computing archi- tecture of marine environment information is proposed, which provides a new cloud technology framework for the integration and sharing of marine environmental information resources. A physical layer, software platform layer and an application layer are illustrated systematically, at the same time, a corresponding solu- tions for many difficult technical problems such as parallel query processing of multi-dimensional, spatio- temporal information, data slice storage, software service flow customization, analysis, reorganization and so on. A prototype system is developed and many different data-size experiments and a comparative analy- sis are done based on it. The experiment results show that the cloud platform based on this framework can achieve high performance and scalability when dealing with large-scale marine data.
基金supported by National Information Security Program under Grant No.2009A112
文摘Security is a key problem for the development of Cloud Computing. A common service security architecture is a basic abstract to support security research work. The authorization ability in the service security faces more complex and variable users and environment. Based on the multidimensional views, the service security architecture is described on three dimensions of service security requirement integrating security attributes and service layers. An attribute-based dynamic access control model is presented to detail the relationships among subjects, objects, roles, attributes, context and extra factors further. The model uses dynamic control policies to support the multiple roles and flexible authority. At last, access control and policies execution mechanism were studied as the implementation suggestion.
文摘After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.
基金the National Key Basic Research Program of China，the National Natural Science Foundation of China，the Ministry of Education of the People's Republic of China，the Fundamental Research Funds for the Central Universities of China
文摘This paper discussed the differences of context-aware service between the cloud computing environment and the traditional service system.Given the above differences,the paper subsequently analyzed the changes of context-aware service during preparation,organization and delivery,as well as the resulting changes in service acceptance of consumers.Because of these changes,the context-aware service modes in the cloud computing environment change are intelligent,immersive,highly interactive,and real-time.According to active and responded service,and authorization and non-authorized service,the paper drew a case diagram of context-aware service in Unified Modeling Language(UML) and established four categories of context-aware service modes.
文摘In the current cloud-based Internet-of-Things （IoT） model, smart devices （such as sensors, smartphones） exchange information through the Internet to cooperate and provide services to users, which could be citizens, smart home systems, and industrial applications.
基金the National Natural Science Foundation of China(Nos.61772130 and 62072096)the Fundamental Research Funds for the Central Universities(No.2232020A-12)+1 种基金the International S&T Cooperation Program of Shanghai Science and Technology Commission(No.20220713000)the Young Top-Notch Talent Program in Shanghai。
文摘The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle applications.Most existing studies focusing on the issue of task offloading in ICVs assume that the MEC server can directly complete computation tasks without considering the necessity of service caching.However,this is unrealistic in practice because a large number of tasks require the use of corresponding third-party libraries and databases,that is,service caching.Therefore,we investigate the delay optimization in an MEC-enabled ICVs system with multiple mobile vehicles,resource-limited base stations(BSs),and one cloud server.We aim to determine the optimal service caching and task offloading decisions to minimize the overall system delay using mixed-integer nonlinear programming.To address this problem,we first convert it into a quadratically constrained quadratic program and then propose an efficient semidefinite relaxation-based joint service caching and task offloading(JSCTO)algorithm to obtain the service caching and task offloading decisions.In the simulations,we validate the efficiency of our proposed method by setting different numbers of vehicles and the storage capacity of BSs.The results show that our proposed JSCTO algorithm can significantly decrease the total delay of all offloaded tasks compared with the cloud processing only scheme.
基金This work was supported by the National Natural Science Foundation of China(Grant:61702048).
文摘With the growing amounts of multi-micro grids,electric vehicles,smart home,smart cities connected to the Power Distribution Internet of Things(PD-IoT)system,greater computing resource and communication bandwidth are required for power distribution.It probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence.This paper presents a service scheduling method based on edge computing to balance the business load of PD-IoT.The architecture,components and functional requirements of the PD-IoT with edge computing platform are proposed.Then,the structure of the service scheduling system is presented.Further,a novel load balancing strategy and ant colony algorithm are investigated in the service scheduling method.The validity of the method is evaluated by simulation tests.Results indicate that the mean load balancing ratio is reduced by 99.16%and the optimized offloading links can be acquired within 1.8 iterations.Computing load of the nodes in edge computing platform can be effectively balanced through the service scheduling.
文摘Cloud computing is becoming a hot topic of the information industry in recent years. Many companies provide the cloud services, such as Google Apps and Apple multimedia services. In general, by applying the virtulization technologies, the data center is built for cloud computing to provide users with the eomputing and storage resources, as well as the software environment. Thus, the quality of service （QoS） must be considered to satisfy users＇ requirements. This paper proposes a high efficiency scheduling scheme for supporting cloud computing. The virtual machine migration technique has been applied to the proposed scheduling scheme for improving the resources utilization and satisfying the QoS requirement of users. The experimental results show that in addition to satisfying the QoS requirement of users, the proposed scheme can improve the resources utilization effectively.
文摘Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloudbased technologies,such as the Internet of Things.With increasing industry adoption and migration of traditional computing services to the cloud,one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies.This work proposes a Data Security Framework for cloud computing services(CCS)that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS.This framework is developed by means of a methodology based on a heuristic theory that incorporates knowledge generated by existing works as well as the experience of their implementation.The paper presents the design details of the framework,which consists of three stages:identification of data security requirements,management of data security risks and evaluation of data security performance in CCS.
基金supported in part by the Industrial Internet Innovation and Development Project "Industrial robot external safety enhancement device"(TC200H030)the Cooperation project between Chongqing Municipal undergraduate universities and institutes affiliated to CAS (HZ2021015)
文摘Mobile edge computing(MEC) is a cloud server running at the edge of a mobile network, which can effectively reduce network communication delay. However, due to the numerous edge servers and devices in the MEC, there may be multiple servers and devices that can provide services to the same user simultaneously. This paper proposes a userside adaptive user service deployment algorithm ASD(Adaptive Service Deployment) based on reinforcement learning algorithms. Without relying on complex system information, it can master only a few tasks and users. In the case of attributes, perform effective service deployment decisions, analyze and redefine the key parameters of existing algorithms, and dynamically adjust strategies according to task types and available node types to optimize user experience delay. Experiments show that the ASD algorithm can implement user-side decision-making for service deployment. While effectively improving parameter settings in the traditional Multi-Armed Bandit algorithm,it can reduce user-perceived delay and enhance service quality compared with other strategies.
文摘Cloud computing is one of the main issues of interest to the scientific community of the spatial data. A cloud is referred to computing infrastructure for a representation of network. From the perspective of providers, the main characteristics of cloud computing is being dynamic, high power in computing and storage. Also cloud computing is a cost benefit and effective way for representation of web-based spatial data and complex analysis. Furthermore, cloud computing is a way to facilitate distributed computing and store different data. One of the main features of cloud computing is ability in powerful computing and dynamic storage with an affordable expense and secure web. In this paper we further investigate the methodologies, services, issues and deployed techniques also, about situation of cloud computing in the past, present and future is probed and some issues concerning the security is expressed. Undoubtedly cloud computing is vital for spatial data infrastructure and consequently the cloud computing is able to expand the interactions for spatial data infrastructure in the future.
基金supported by Jilin Provincial Science and Technology Department Natural Science Foundation of China(20210101415JC)Jilin Provincial Science and Technology Department Free exploration research project of China(YDZJ202201ZYTS642).
文摘Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.
基金Project (No. 05SN07114) supported by the International Cooperation Project of the Shanghai Science and Technology Commission of China and the National Research Council of Canada
文摘Mobility and resource-limitedness pose challenging issues to service configuration for quality of service (QoS) management in ubiquitous computing environments. Previous configuration approaches, such as static resource reservation, dynamic resource allocation and single service composition are not valid in the environments. In this study, we present an adaptive service configuration approach. Firstly, we reduce the dynamic configuration process to a control model which aims to achieve the variation of critical QoS on minimal level with less resource cost. Secondly, to deal with different QoS variations, we design two configuration strategies—service chain reconfiguration and QoS parameter adjustment—and implement them based on fuzzy logic control theory. Finally, a configuration algorithm is developed to flexibly employ the two configuration strategies in tune with the error of critical QoS in configuration process. The results of simulation experiments suggest that our approach outper- forms existing configuration approaches in both QoS improvement and resource utilization.
文摘Cloud computing is high technology, which fulfills needs of common as well as enterprise level to meet their information and communication technology requirements and so on. Cloud computing extends existing information technology capabilities and requirements. Many technologies are being merged with cloud computing, same as that orchestrations can boost cloud service provisioning process. The usage of orchestrations can play vital role to provision cloud services. Cloud service providers can create scalable cloud services at low cost by organizing cloud infrastructure by using cloud orchestrations. Dynamic orchestration flows can generate required cloud computing services to meet service level agreements and quality of services. There is a need to understand issues and barriers involved to integrate cloud orchestrations with cloud service provisioning process. There is also need to understand business related problems bordering cloud computing technology. There is much capacity to do targeted research work for cloud orchestrations and its integration with service level agreements as well as with SLI (service level integration) layer. In this article we have elaborated detailed analysis and identified a number of issues that will affect the cloud service users as well as cloud service providers and cloud service provisioning system. We are defining an approach to orchestrate cloud infrastructure by using orchestration flows, to generate cloud services in order to meet service level agreements and quality of standard.
文摘Enhancements in technology always follow Consumer requirements. Consumer requires best of service with least possible mismatch and on time. Numerous applications available today are based on Web Services and Cloud Computing. Recently, there exist many Web Services with similar functional characteristics. Choosing “a-right” Service from group of similar Web Service is a complicated task for Service Consumer. In that case, Service Consumer can discover the required Web Service using non functional attributes of the Web Services such as QoS. Proposed layered architecture and Web Service-Cloud, i.e. WS-Cloud computing Framework synthesizes the non functional attributes that includes reliability, availability, response time, latency etc. The Service Consumer is projected to provide the QoS requirements as part of Service discovery query. This framework will discover and filter the Web Services form the cloud and rank them according to Service Consumer preferences to facilitate Service on time.
文摘Big Data applications are pervading more and more aspects of our life, encompassing commercial and scientific uses at increasing rates as we move towards exascale analytics. Examples of Big Data applications include storing and accessing user data in commercial clouds, mining of social data, and analysis of large-scale simulations and experiments such as the Large Hadron Collider. An increasing number of such data—intensive applications and services are relying on clouds in order to process and manage the enormous amounts of data required for continuous operation. It can be difficult to decide which of the many options for cloud processing is suitable for a given application;the aim of this paper is therefore to provide an interested user with an overview of the most important concepts of cloud computing as it relates to processing of Big Data.
