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
At present,most providers of cloud computing mainly provide infrastructures and services of infrastructure as a service(IaaS).But there is a serious problem that is the lack of security standards and evaluation model ...At present,most providers of cloud computing mainly provide infrastructures and services of infrastructure as a service(IaaS).But there is a serious problem that is the lack of security standards and evaluation model of IaaS.After analyzing the vulnerabilities performance of IaaS cloud computing system,the mapping relationship was established between the vulnerabilities of IaaS and the nine threats of cloud computing which was released by cloud security alliance(CSA).According to the mapping relationship,a model for evaluating security of IaaS was proposed which verified the effectiveness of the model on OpenStack by the analytic hierarchy process(AHP) and the fuzzy evaluation method.展开更多
In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to im...In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.展开更多
On-demand availability and resource elasticity features of Cloud computing have attracted the focus of various research domains.Mobile cloud computing is one of these domains where complex computation tasks are offloa...On-demand availability and resource elasticity features of Cloud computing have attracted the focus of various research domains.Mobile cloud computing is one of these domains where complex computation tasks are offloaded to the cloud resources to augment mobile devices’cognitive capacity.However,the flexible provisioning of cloud resources is hindered by uncertain offloading workloads and significant setup time of cloud virtual machines(VMs).Furthermore,any delays at the cloud end would further aggravate the miseries of real-time tasks.To resolve these issues,this paper proposes an auto-scaling framework(ACF)that strives to maintain the quality of service(QoS)for the end users as per the service level agreement(SLA)negotiated assurance level for service availability.In addition,it also provides an innovative solution for dealing with the VM startup overheads without truncating the running tasks.Unlike the waiting cost and service cost tradeoff-based systems or threshold-rule-based systems,it does not require strict tuning in the waiting costs or in the threshold rules for enhancing the QoS.We explored the design space of the ACF system with the CloudSim simulator.The extensive sets of experiments demonstrate the effectiveness of the ACF system in terms of good reduction in energy dissipation at the mobile devices and improvement in the QoS.At the same time,the proposed ACF system also reduces the monetary costs of the service providers.展开更多
Despite the rapid advances in mobile technology, many constraints still prevent mobile devices from running resource-demanding applications in mobile environments. Cloud computing with flexibility, stability and scala...Despite the rapid advances in mobile technology, many constraints still prevent mobile devices from running resource-demanding applications in mobile environments. Cloud computing with flexibility, stability and scalability enables access to unlimited resources for mobile devices, so more studies have focused on cloud computingbased mobile services. Due to the stability of wireless networks, changes of Quality of Service （QoS） level and user＇ real-time preferences, it is becoming challenging to determine how to adaptively choose the ＂appropriate＂ service in mobile cloud computing environments. In this paper, we present an adaptive service selection method. This method first extracts user preferences from a service＇s evaluation and calculates the similarity of the service with the weighted Euclidean distance. Then, they are combined with user context data and the most suitable service is recommended to the user. In addition, we apply the fuzzy cognitive imps-based model to the adaptive policy, which improves the efficiency and performance of the algorithm. Finally, the experiment and simulation demonstrate that our approach is effective.展开更多
A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices.It can significantly reduce the access delay for mobile application users.However,the high user mobilit...A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices.It can significantly reduce the access delay for mobile application users.However,the high user mobility brings significant challenges to the service provisioning for mobile users,especially to delay-sensitive mobile applications.With the objective to maximize a profit,which positively associates with the overall admitted traffic served by the local edge cloud,and negatively associates with the access delay as well as virtual machine migration delay,we study a fundamental problem in this paper:how to update the service provisioning solution for a given group of mobile users.Such a profit-maximization problem is formulated as a nonlinear integer linear programming and linearized by absolute value manipulation techniques.Then,we propose a framework of heuristic algorithms to solve this Nondeterministic Polynomial(NP)-hard problem.The numerical simulation results demonstrate the efficiency of the devised algorithms.Some useful summaries are concluded via the analysis of evaluation results.展开更多
With network developing and virtualization rising, more and more indoor environment （POIs） such as care, library, office, even bus and subway can provide plenty of bandwidth and computing resources. Meanwhile many p...With network developing and virtualization rising, more and more indoor environment （POIs） such as care, library, office, even bus and subway can provide plenty of bandwidth and computing resources. Meanwhile many people daily spending much time in them are still suffering from the mobile device with limited resources. This situation implies a novel local cloud computing paradigm in which mobile device can leverage nearby resources to facilitate task execution. In this paper, we implement a mobile local computing system based on indoor virtual cloud. This system mainly contains three key components： 1）As to application, we create a parser to generate the ＂method call and cost tree＂ and analyze it to identify resource- intensive methods. 2） As to mobile device, we design a self-learning execution controller to make offtoading decision at runtime. 3） As to cloud, we construct a social scheduling based application-isolation virtual cloud model. The evaluation results demonstrate that our system is effective and efficient by evaluating CPU- intensive calculation application, Memory- intensive image translation application and I/ O-intensive image downloading application.展开更多
Cloud computing provides a new paradigm for hardware and software infrastructure design as well as planning and usage of information systems. It offers flexible, efficient, inexpensive, and quality services. This pape...Cloud computing provides a new paradigm for hardware and software infrastructure design as well as planning and usage of information systems. It offers flexible, efficient, inexpensive, and quality services. This paper proposes an on-demand service system using the cloud computing architecture and analyzes important issues such as organization, management, and monitoring of distributed service resources; context-aware on-demand service modeling, on-demand automated service composition in large-scale networks, and service system analysis based on complex system theory. Continuous Operating Reference Station （CORS） of a geo-spatial information system is taken as an example, and its architecture is analyzed from the perspective of cloud computing. Some fundamental questions are raised about its service.展开更多
In a traditional Mobile Cloud Computing (MCC), a stream of data produced by mobile users (MUs) is uploaded to the remote cloud for additional processing throughout the Internet. Though, due to long WAN distance it cau...In a traditional Mobile Cloud Computing (MCC), a stream of data produced by mobile users (MUs) is uploaded to the remote cloud for additional processing throughout the Internet. Though, due to long WAN distance it causes high End to End latency. With the intention of minimize the average response time and key constrained Service Delay (network and cloudlet Delay) for mobile users (MUs), offload their workloads to the geographically distributed cloudlets network, we propose the Multi-layer Latency Aware Workload Assignment Strategy (MLAWAS) to allocate MUs workloads into optimal cloudlets, Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with two other existing strategies.展开更多
New paradigms for processing and storing data such as cloud computing require new approaches for the measurement of cloud service performance. To establish a Service Level Agreement (SLA) between a cloud service provi...New paradigms for processing and storing data such as cloud computing require new approaches for the measurement of cloud service performance. To establish a Service Level Agreement (SLA) between a cloud service provider and its customers, the cloud services and their service level objectives need to be identified. An additional challenge in the performance measurement of cloud services is the lack of models that integrate the different perspectives of providers, maintainers and customers within the same model in order to define the concepts commonly used in cloud SLA contracts. This work proposes a three-dimensional Performance Measurement Model for Cloud Computing (P2M2C-3D) which consolidates performance measurement from the perspectives of providers, maintainers and customers for the different types of cloud services.展开更多
In recent years,the use of mobile devices such as smart phones,tablet PCs,etc.is rapidly increasing.In case of these mobile devices,the storage space is limited due to their characteristics.To make up for the limited ...In recent years,the use of mobile devices such as smart phones,tablet PCs,etc.is rapidly increasing.In case of these mobile devices,the storage space is limited due to their characteristics.To make up for the limited space of storage in mobile devices,several methods are being researched.Of these,cloud storage service(CSS),one of cloud computing services,is an efficient solution to compensate such limited storage space.CSS is a service of storing files to the storage and thus getting access to stored files through networks(Internet)at anytime,anywhere.As for the existing CSS,users store their personally important files in the cloud storage,not in their own computers.It may cause security problems such as the leaking of information from private files or the damaging to the information.Thus,we propose a cloud storage system which can solve the security problem of CSS for mobile devices using the personal computer.Our system is deigned to store and manage files through the direct communication between mobile devices and personal computer storages by using the software as a service(SaaS),one of computing services,instead of directly storing files into cloud storages.展开更多
In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only conside...In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only.This paper presents a novel comprehensive utility function for resource allocation in MEC.The utility function considers the heterogeneous nature of applications that a UE offloads to MES.The proposed utility function considers all important parameters,including CPU,RAM,hard disk space,required time,and distance,to calculate a more realistic utility value for MESs.Moreover,we improve upon some general algorithms,used for resource allocation in MEC and cloud computing,by considering our proposed utility function.We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes.The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources.The utility function depends upon the UE requests and the distance between UEs and MES,and serves as a realistic means of comparison between different types of UE requests.Choosing(or selecting)an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task.We show that MES resource allocation is sub-optimal if CPU is the only resource considered.By taking into account the other resources,i.e.,RAM,disk space,request time,and distance in the utility function,we demonstrate improvement in the resource allocation algorithms in terms of service rate,utility,and MES energy consumption.展开更多
This survey paper provides a general overview on Cloud Computing. The topics that are discussed include characteristics, deployment and service models as well drawbacks. Major aspects of Cloud Computing are explained ...This survey paper provides a general overview on Cloud Computing. The topics that are discussed include characteristics, deployment and service models as well drawbacks. Major aspects of Cloud Computing are explained to give the reader a clearer understanding on the complexity of the platform. Following this, several security issues and countermeasures are also discussed to show the major issues and obstacles that Cloud Computing faces as it is being implemented further. The major part of countermeasures focuses on Intrusion Detection Systems. Moving towards Mobile Cloud Computing and Internet of Things, this survey paper gives a general explanation on the applications and potential that comes with the integration of Cloud Computing with any device that has Internet connectivity as well as the challenges that are before it.展开更多
Cryptography as a service is becoming extremely popular. It eases the way companies deal with securing their information without having to worry about their customer’s information being accessed by someone who should...Cryptography as a service is becoming extremely popular. It eases the way companies deal with securing their information without having to worry about their customer’s information being accessed by someone who should not have access to it. In this overview, we will be taking a closer look at Cryptography as a Service. The ground we will be examining is the effectiveness of it for mobile/wireless and desktop computing. Since we will be looking at something that operates as a service, we will need to first cover the application program interface (API) basics [1] or standard software as a service (SaaS) [2]. Next, what exactly cryptography as a service means for each of the aforementioned platforms. Lastly, other possible solutions and how they compare to CaaS. For the purpose of this review, we will be looking at CaaS in a cloud environment since typical SaaS is used that way. Subsequently most cloud environments utilize a UNIX based operating system or similar solution, which will be the target environment for the purpose of this paper. Popular algorithms that are used in CaaS will be the final part that will be examined on the grounds of how they perform, level of security offered, and usability in CaaS. Upon reading this paper the reader will have a better understanding of how exactly CaaS operates and what it has to offer for mobile, desktop, and wireless users in the present and future.展开更多
Information and communication technology （ICT） and systems are essential for every business. They can be used in retail, manufacturing and other industries. Nevertheless, new and innovative ideas and solutions are c...Information and communication technology （ICT） and systems are essential for every business. They can be used in retail, manufacturing and other industries. Nevertheless, new and innovative ideas and solutions are constantly emerging and introducing new possibilities for the reorganization of traditional logistics processes. Particularly, attention is given to basic concept of CC （cloud computing） service models and opportunities in logistics. This paper provides comprehensive review and comparison of different ICT solutions and CC applications. As a new and cutting-edge technology, CC is changing the form and function of information technology infrastructures making supply chain information collaboration easy and feasible. It can also be an enabler of fully electronic logistics management systems. Adoption of CC concept involves strong hardware support, good internet connectivity and implied reorganization of traditional business activities.展开更多
Mobile cloud computing （MCC） has become a promising technique to deal with computation- or data-intensive tasks. It overcomes the limited processing power, poor storage capacity, and short battery life of mobile dev...Mobile cloud computing （MCC） has become a promising technique to deal with computation- or data-intensive tasks. It overcomes the limited processing power, poor storage capacity, and short battery life of mobile devices. Providing continuous and on-demand services, MCC argues that the service must be available for users at anytime and anywhere. However, at present, the service availability of MCC is usually measured by some certain metrics of a real-world system, and the results do not have broad representation since different systems have different load levels, different deployments, and many other random factors. Meanwhile, for large-scale and complex types of services in MCC systems, simulation-based methods （such as Monte- Carlo simulation） may be costly and the traditional state-based methods always suffer from the problem of state-space explosion. In this paper, to overcome these shortcomings, fluid-flow approximation, a breakthrough to avoid state-space explosion, is adopted to analyze the service availability of MCC. Four critical metrics, including response time of service, minimum sensing time of devices, minimum number of nodes chosen, and action throughput, are def＇med to estimate the availability by solving a group of ordinary differential equations even before the MCC system is fully deployed. Experimental results show that our method costs less time in analyzing the service availability of MCC than the Markov- or simulation-based methods.展开更多
Cloud computing has been considered as the next-generation computing platform with the potential to address the data and computing challenges in geosciences.However,only a limited number of geoscientists have been ada...Cloud computing has been considered as the next-generation computing platform with the potential to address the data and computing challenges in geosciences.However,only a limited number of geoscientists have been adapting this platform for their scientific research mainly due to two barriers:1)selecting an appropriate cloud platform for a specific application could be challenging,as various cloud services are available and 2)existing general cloud platforms are not designed to support geoscience applications,algorithms and models.To tackle such barriers,this research aims to design a hybrid cloud computing(HCC)platform that can utilize and integrate the computing resources across different organizations to build a unified geospatial cloud computing platform.This platform can manage different types of underlying cloud infrastructure(e.g.,private or public clouds),and enables geoscientists to test and leverage the cloud capabilities through a web interface.Additionally,the platform also provides different geospatial cloud services,such as workflow as a service,on the top of common cloud services(e.g.,infrastructure as a service)provided by general cloud platforms.Therefore,geoscientists can easily create a model workflow by recruiting the needed models for a geospatial application or task on the fly.A HCC prototype is developed and dust storm simulation is used to demonstrate the capability and feasibility of such platform in facilitating geosciences by leveraging across-organization computing and model resources.展开更多
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National Natural Science Foundation of China(No.61462070)the"ChunHui Plan"Project of Educational Department,China(No.Z2009-1-01062)the Research of Evaluation Technology of Security and Reliability of Cloud Computing and the Built of Testing Platform That is a Technology Plan Project of Inner Mongolia,China
文摘At present,most providers of cloud computing mainly provide infrastructures and services of infrastructure as a service(IaaS).But there is a serious problem that is the lack of security standards and evaluation model of IaaS.After analyzing the vulnerabilities performance of IaaS cloud computing system,the mapping relationship was established between the vulnerabilities of IaaS and the nine threats of cloud computing which was released by cloud security alliance(CSA).According to the mapping relationship,a model for evaluating security of IaaS was proposed which verified the effectiveness of the model on OpenStack by the analytic hierarchy process(AHP) and the fuzzy evaluation method.
基金supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIT) (No.2021R1C1C1013133)supported by the Institute of Information and Communications Technology Planning and Evaluation (IITP)grant funded by the Korea Government (MSIT) (RS-2022-00167197,Development of Intelligent 5G/6G Infrastructure Technology for The Smart City)supported by the Soonchunhyang University Research Fund.
文摘In many IIoT architectures,various devices connect to the edge cloud via gateway systems.For data processing,numerous data are delivered to the edge cloud.Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency.There are two types of costs for this kind of IoT network:a communication cost and a computing cost.For service efficiency,the communication cost of data transmission should be minimized,and the computing cost in the edge cloud should be also minimized.Therefore,in this paper,the communication cost for data transmission is defined as the delay factor,and the computing cost in the edge cloud is defined as the waiting time of the computing intensity.The proposed method selects an edge cloud that minimizes the total cost of the communication and computing costs.That is,a device chooses a routing path to the selected edge cloud based on the costs.The proposed method controls the data flows in a mesh-structured network and appropriately distributes the data processing load.The performance of the proposed method is validated through extensive computer simulation.When the transition probability from good to bad is 0.3 and the transition probability from bad to good is 0.7 in wireless and edge cloud states,the proposed method reduced both the average delay and the service pause counts to about 25%of the existing method.
基金This research work is funded by TEQIP-III under Assistantship Head:1.3.2.2 in PFMS dated 29.06.2021.
文摘On-demand availability and resource elasticity features of Cloud computing have attracted the focus of various research domains.Mobile cloud computing is one of these domains where complex computation tasks are offloaded to the cloud resources to augment mobile devices’cognitive capacity.However,the flexible provisioning of cloud resources is hindered by uncertain offloading workloads and significant setup time of cloud virtual machines(VMs).Furthermore,any delays at the cloud end would further aggravate the miseries of real-time tasks.To resolve these issues,this paper proposes an auto-scaling framework(ACF)that strives to maintain the quality of service(QoS)for the end users as per the service level agreement(SLA)negotiated assurance level for service availability.In addition,it also provides an innovative solution for dealing with the VM startup overheads without truncating the running tasks.Unlike the waiting cost and service cost tradeoff-based systems or threshold-rule-based systems,it does not require strict tuning in the waiting costs or in the threshold rules for enhancing the QoS.We explored the design space of the ACF system with the CloudSim simulator.The extensive sets of experiments demonstrate the effectiveness of the ACF system in terms of good reduction in energy dissipation at the mobile devices and improvement in the QoS.At the same time,the proposed ACF system also reduces the monetary costs of the service providers.
基金the third level of 2011 Zhejiang Province 151 Talent Project and National Natural Science Foundation of China under Grant No.61100043
文摘Despite the rapid advances in mobile technology, many constraints still prevent mobile devices from running resource-demanding applications in mobile environments. Cloud computing with flexibility, stability and scalability enables access to unlimited resources for mobile devices, so more studies have focused on cloud computingbased mobile services. Due to the stability of wireless networks, changes of Quality of Service （QoS） level and user＇ real-time preferences, it is becoming challenging to determine how to adaptively choose the ＂appropriate＂ service in mobile cloud computing environments. In this paper, we present an adaptive service selection method. This method first extracts user preferences from a service＇s evaluation and calculates the similarity of the service with the weighted Euclidean distance. Then, they are combined with user context data and the most suitable service is recommended to the user. In addition, we apply the fuzzy cognitive imps-based model to the adaptive policy, which improves the efficiency and performance of the algorithm. Finally, the experiment and simulation demonstrate that our approach is effective.
基金partially supported by JSPS KAKENHI under Grant Number JP16J07062
文摘A mobile edge cloud provides a platform to accommodate the offloaded traffic workload generated by mobile devices.It can significantly reduce the access delay for mobile application users.However,the high user mobility brings significant challenges to the service provisioning for mobile users,especially to delay-sensitive mobile applications.With the objective to maximize a profit,which positively associates with the overall admitted traffic served by the local edge cloud,and negatively associates with the access delay as well as virtual machine migration delay,we study a fundamental problem in this paper:how to update the service provisioning solution for a given group of mobile users.Such a profit-maximization problem is formulated as a nonlinear integer linear programming and linearized by absolute value manipulation techniques.Then,we propose a framework of heuristic algorithms to solve this Nondeterministic Polynomial(NP)-hard problem.The numerical simulation results demonstrate the efficiency of the devised algorithms.Some useful summaries are concluded via the analysis of evaluation results.
基金ACKNOWLEDGEMENTS This work was supported by the Research Fund for the Doctoral Program of Higher Education of China （No.20110031110026 and No.20120031110035）, the National Natural Science Foundation of China （No. 61103214）, and the Key Project in Tianjin Science ＆ Technology Pillar Program （No. 13ZCZDGX01098）.
文摘With network developing and virtualization rising, more and more indoor environment （POIs） such as care, library, office, even bus and subway can provide plenty of bandwidth and computing resources. Meanwhile many people daily spending much time in them are still suffering from the mobile device with limited resources. This situation implies a novel local cloud computing paradigm in which mobile device can leverage nearby resources to facilitate task execution. In this paper, we implement a mobile local computing system based on indoor virtual cloud. This system mainly contains three key components： 1）As to application, we create a parser to generate the ＂method call and cost tree＂ and analyze it to identify resource- intensive methods. 2） As to mobile device, we design a self-learning execution controller to make offtoading decision at runtime. 3） As to cloud, we construct a social scheduling based application-isolation virtual cloud model. The evaluation results demonstrate that our system is effective and efficient by evaluating CPU- intensive calculation application, Memory- intensive image translation application and I/ O-intensive image downloading application.
基金funded by the National Basic Research Program of China ("973" Program) under Grant No. 2007CB310805the National High Technology Research and Development Program of China ("863" Program) under Grant No. 2007AA12Z309
文摘Cloud computing provides a new paradigm for hardware and software infrastructure design as well as planning and usage of information systems. It offers flexible, efficient, inexpensive, and quality services. This paper proposes an on-demand service system using the cloud computing architecture and analyzes important issues such as organization, management, and monitoring of distributed service resources; context-aware on-demand service modeling, on-demand automated service composition in large-scale networks, and service system analysis based on complex system theory. Continuous Operating Reference Station （CORS） of a geo-spatial information system is taken as an example, and its architecture is analyzed from the perspective of cloud computing. Some fundamental questions are raised about its service.
文摘In a traditional Mobile Cloud Computing (MCC), a stream of data produced by mobile users (MUs) is uploaded to the remote cloud for additional processing throughout the Internet. Though, due to long WAN distance it causes high End to End latency. With the intention of minimize the average response time and key constrained Service Delay (network and cloudlet Delay) for mobile users (MUs), offload their workloads to the geographically distributed cloudlets network, we propose the Multi-layer Latency Aware Workload Assignment Strategy (MLAWAS) to allocate MUs workloads into optimal cloudlets, Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with two other existing strategies.
文摘New paradigms for processing and storing data such as cloud computing require new approaches for the measurement of cloud service performance. To establish a Service Level Agreement (SLA) between a cloud service provider and its customers, the cloud services and their service level objectives need to be identified. An additional challenge in the performance measurement of cloud services is the lack of models that integrate the different perspectives of providers, maintainers and customers within the same model in order to define the concepts commonly used in cloud SLA contracts. This work proposes a three-dimensional Performance Measurement Model for Cloud Computing (P2M2C-3D) which consolidates performance measurement from the perspectives of providers, maintainers and customers for the different types of cloud services.
基金The MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support programsupervised by the NIPA(National ITIndustry Promotion Agency)(NIPA-2012-H0301-12-2006)
文摘In recent years,the use of mobile devices such as smart phones,tablet PCs,etc.is rapidly increasing.In case of these mobile devices,the storage space is limited due to their characteristics.To make up for the limited space of storage in mobile devices,several methods are being researched.Of these,cloud storage service(CSS),one of cloud computing services,is an efficient solution to compensate such limited storage space.CSS is a service of storing files to the storage and thus getting access to stored files through networks(Internet)at anytime,anywhere.As for the existing CSS,users store their personally important files in the cloud storage,not in their own computers.It may cause security problems such as the leaking of information from private files or the damaging to the information.Thus,we propose a cloud storage system which can solve the security problem of CSS for mobile devices using the personal computer.Our system is deigned to store and manage files through the direct communication between mobile devices and personal computer storages by using the software as a service(SaaS),one of computing services,instead of directly storing files into cloud storages.
基金National Research Foundation of Korea-Grant funded by the Korean Government(Ministry of Science and ICT)-NRF-2020R1AB5B02002478.
文摘In mobile edge computing(MEC),one of the important challenges is how much resources of which mobile edge server(MES)should be allocated to which user equipment(UE).The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only.This paper presents a novel comprehensive utility function for resource allocation in MEC.The utility function considers the heterogeneous nature of applications that a UE offloads to MES.The proposed utility function considers all important parameters,including CPU,RAM,hard disk space,required time,and distance,to calculate a more realistic utility value for MESs.Moreover,we improve upon some general algorithms,used for resource allocation in MEC and cloud computing,by considering our proposed utility function.We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes.The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources.The utility function depends upon the UE requests and the distance between UEs and MES,and serves as a realistic means of comparison between different types of UE requests.Choosing(or selecting)an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task.We show that MES resource allocation is sub-optimal if CPU is the only resource considered.By taking into account the other resources,i.e.,RAM,disk space,request time,and distance in the utility function,we demonstrate improvement in the resource allocation algorithms in terms of service rate,utility,and MES energy consumption.
文摘This survey paper provides a general overview on Cloud Computing. The topics that are discussed include characteristics, deployment and service models as well drawbacks. Major aspects of Cloud Computing are explained to give the reader a clearer understanding on the complexity of the platform. Following this, several security issues and countermeasures are also discussed to show the major issues and obstacles that Cloud Computing faces as it is being implemented further. The major part of countermeasures focuses on Intrusion Detection Systems. Moving towards Mobile Cloud Computing and Internet of Things, this survey paper gives a general explanation on the applications and potential that comes with the integration of Cloud Computing with any device that has Internet connectivity as well as the challenges that are before it.
文摘Cryptography as a service is becoming extremely popular. It eases the way companies deal with securing their information without having to worry about their customer’s information being accessed by someone who should not have access to it. In this overview, we will be taking a closer look at Cryptography as a Service. The ground we will be examining is the effectiveness of it for mobile/wireless and desktop computing. Since we will be looking at something that operates as a service, we will need to first cover the application program interface (API) basics [1] or standard software as a service (SaaS) [2]. Next, what exactly cryptography as a service means for each of the aforementioned platforms. Lastly, other possible solutions and how they compare to CaaS. For the purpose of this review, we will be looking at CaaS in a cloud environment since typical SaaS is used that way. Subsequently most cloud environments utilize a UNIX based operating system or similar solution, which will be the target environment for the purpose of this paper. Popular algorithms that are used in CaaS will be the final part that will be examined on the grounds of how they perform, level of security offered, and usability in CaaS. Upon reading this paper the reader will have a better understanding of how exactly CaaS operates and what it has to offer for mobile, desktop, and wireless users in the present and future.
文摘Information and communication technology （ICT） and systems are essential for every business. They can be used in retail, manufacturing and other industries. Nevertheless, new and innovative ideas and solutions are constantly emerging and introducing new possibilities for the reorganization of traditional logistics processes. Particularly, attention is given to basic concept of CC （cloud computing） service models and opportunities in logistics. This paper provides comprehensive review and comparison of different ICT solutions and CC applications. As a new and cutting-edge technology, CC is changing the form and function of information technology infrastructures making supply chain information collaboration easy and feasible. It can also be an enabler of fully electronic logistics management systems. Adoption of CC concept involves strong hardware support, good internet connectivity and implied reorganization of traditional business activities.
基金Project supported by the National Natural Science Foundation of China （Nos. 61402127 and 61370212） and the Natural Science Foundation of Heilongjiang Province, China （No. F2015029）
文摘Mobile cloud computing （MCC） has become a promising technique to deal with computation- or data-intensive tasks. It overcomes the limited processing power, poor storage capacity, and short battery life of mobile devices. Providing continuous and on-demand services, MCC argues that the service must be available for users at anytime and anywhere. However, at present, the service availability of MCC is usually measured by some certain metrics of a real-world system, and the results do not have broad representation since different systems have different load levels, different deployments, and many other random factors. Meanwhile, for large-scale and complex types of services in MCC systems, simulation-based methods （such as Monte- Carlo simulation） may be costly and the traditional state-based methods always suffer from the problem of state-space explosion. In this paper, to overcome these shortcomings, fluid-flow approximation, a breakthrough to avoid state-space explosion, is adopted to analyze the service availability of MCC. Four critical metrics, including response time of service, minimum sensing time of devices, minimum number of nodes chosen, and action throughput, are def＇med to estimate the availability by solving a group of ordinary differential equations even before the MCC system is fully deployed. Experimental results show that our method costs less time in analyzing the service availability of MCC than the Markov- or simulation-based methods.
文摘Cloud computing has been considered as the next-generation computing platform with the potential to address the data and computing challenges in geosciences.However,only a limited number of geoscientists have been adapting this platform for their scientific research mainly due to two barriers:1)selecting an appropriate cloud platform for a specific application could be challenging,as various cloud services are available and 2)existing general cloud platforms are not designed to support geoscience applications,algorithms and models.To tackle such barriers,this research aims to design a hybrid cloud computing(HCC)platform that can utilize and integrate the computing resources across different organizations to build a unified geospatial cloud computing platform.This platform can manage different types of underlying cloud infrastructure(e.g.,private or public clouds),and enables geoscientists to test and leverage the cloud capabilities through a web interface.Additionally,the platform also provides different geospatial cloud services,such as workflow as a service,on the top of common cloud services(e.g.,infrastructure as a service)provided by general cloud platforms.Therefore,geoscientists can easily create a model workflow by recruiting the needed models for a geospatial application or task on the fly.A HCC prototype is developed and dust storm simulation is used to demonstrate the capability and feasibility of such platform in facilitating geosciences by leveraging across-organization computing and model resources.
