A key issue for Cloud Computing data-centers is to maximize their profits by minimizing power consumption and SLA violations of hosted applications. In this paper, we propose a resource management framework combining a utility-based dynamic Virtual Machine provisioning manager and a dynamic VM placement manager. Both problems are modeled as constraint satisfaction problems. The VM provisioning process aims at maximizing a global utility capturing both the performance of the hosted applications with regard to their SLAs and the energy-related operational cost of the cloud computing infrastructure. We show several experiments how our system can be controlled through high level handles to make different trade-off between application performance and energy consumption or to arbitrate resource allocations in case of contention.
{"title":"Performance and Power Management for Cloud Infrastructures","authors":"H. N. Van, F. Tran, Jean-Marc Menaud","doi":"10.1109/CLOUD.2010.25","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.25","url":null,"abstract":"A key issue for Cloud Computing data-centers is to maximize their profits by minimizing power consumption and SLA violations of hosted applications. In this paper, we propose a resource management framework combining a utility-based dynamic Virtual Machine provisioning manager and a dynamic VM placement manager. Both problems are modeled as constraint satisfaction problems. The VM provisioning process aims at maximizing a global utility capturing both the performance of the hosted applications with regard to their SLAs and the energy-related operational cost of the cloud computing infrastructure. We show several experiments how our system can be controlled through high level handles to make different trade-off between application performance and energy consumption or to arbitrate resource allocations in case of contention.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121686347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing, a new paradigm of distributed computing, introduces many new ideas, concepts, principals, technologies and architectural styles into enterprise service-oriented computing. The enterprise service-oriented architecture (ESOA) style is an abstraction of concrete enterprise service-orientated architectures, which includes SOA architectural elements, service design patterns as well as principles, and SOA quality attributes. It can be extended to a new style for realizing enterprise cloud computing. Meanwhile, the principles and style of enterprise service-oriented computing facilitate the enterprise-wide adoption of cloud computing. This paper extends the ESOA style to a new hybrid architectural style, Enterprise Cloud Service Architecture (ECSA). The style is described by extending enterprise service-oriented formula for ESOA. We model the style through specifying each element in the formula with both service-oriented and cloud architectural styles.
{"title":"Enterprise Cloud Service Architecture","authors":"Longji Tang, Jing Dong, Yajing Zhao, Liang-Jie Zhang","doi":"10.1109/CLOUD.2010.10","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.10","url":null,"abstract":"Cloud computing, a new paradigm of distributed computing, introduces many new ideas, concepts, principals, technologies and architectural styles into enterprise service-oriented computing. The enterprise service-oriented architecture (ESOA) style is an abstraction of concrete enterprise service-orientated architectures, which includes SOA architectural elements, service design patterns as well as principles, and SOA quality attributes. It can be extended to a new style for realizing enterprise cloud computing. Meanwhile, the principles and style of enterprise service-oriented computing facilitate the enterprise-wide adoption of cloud computing. This paper extends the ESOA style to a new hybrid architectural style, Enterprise Cloud Service Architecture (ECSA). The style is described by extending enterprise service-oriented formula for ESOA. We model the style through specifying each element in the formula with both service-oriented and cloud architectural styles.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134528471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Infrastructure resources on-demand requires resource provision (e.g., CPU and memory) to be both sufficient and necessary, which is the most important issue and a challenge in Cloud Computing. Platform as a service (PaaS) encapsulates a layer of software that includes middleware, and even development environment, and provides them as a service for building and deploying cloud applications. In PaaS, the issue of on-demand infrastructure resource management becomes more challenging due to the thousands of cloud applications that share and compete for resources simultaneously. The fundamental solution is to integrate and coordinate the resource consumption and allocation management of a cloud application. The difficulties of such a solution in PaaS are essentially how to maximize the resource utilization of an application, and how to allocate resources to guarantee adequate resource provision for the system. In this paper, we propose an approach to managing infrastructure resources in PaaS by leveraging two adaptive control loops: the resource consumption optimization loop and the resource allocation loop. The optimization loop improves the resource utilization of a cloud application via management functions provided by the corresponding middleware layers of PaaS. The allocation loop provides or reclaims appropriate amounts of resources to/from the application system while guaranteeing its performance. The two loops are integrated to run consecutively and repeatedly to provide infrastructure resources on-demand by first trying to improve resource utilization, and then allocating more resources when necessary. We implement a framework, SmartRod, to investigate our approach. The experiment on SmartRod proves its effectiveness on infrastructure resource management.
{"title":"Integrating Resource Consumption and Allocation for Infrastructure Resources on-Demand","authors":"Y. Zhang, Gang Huang, Xuanzhe Liu, Hong Mei","doi":"10.1109/CLOUD.2010.11","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.11","url":null,"abstract":"Infrastructure resources on-demand requires resource provision (e.g., CPU and memory) to be both sufficient and necessary, which is the most important issue and a challenge in Cloud Computing. Platform as a service (PaaS) encapsulates a layer of software that includes middleware, and even development environment, and provides them as a service for building and deploying cloud applications. In PaaS, the issue of on-demand infrastructure resource management becomes more challenging due to the thousands of cloud applications that share and compete for resources simultaneously. The fundamental solution is to integrate and coordinate the resource consumption and allocation management of a cloud application. The difficulties of such a solution in PaaS are essentially how to maximize the resource utilization of an application, and how to allocate resources to guarantee adequate resource provision for the system. In this paper, we propose an approach to managing infrastructure resources in PaaS by leveraging two adaptive control loops: the resource consumption optimization loop and the resource allocation loop. The optimization loop improves the resource utilization of a cloud application via management functions provided by the corresponding middleware layers of PaaS. The allocation loop provides or reclaims appropriate amounts of resources to/from the application system while guaranteeing its performance. The two loops are integrated to run consecutively and repeatedly to provide infrastructure resources on-demand by first trying to improve resource utilization, and then allocating more resources when necessary. We implement a framework, SmartRod, to investigate our approach. The experiment on SmartRod proves its effectiveness on infrastructure resource management.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133862556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Azeez, S. Perera, Dimuthu Gamage, Ruwan Linton, Prabath Siriwardana, Dimuthu Leelaratne, S. Weerawarana, Paul Fremantle
Enterprise IT infrastructure incurs many costs ranging from hardware costs and software licenses/maintenance costs to the costs of monitoring, managing, and maintaining IT infrastructure. The recent advent of cloud computing offers some tangible prospects of reducing some of those costs; however, abstractions provided by cloud computing are often inadequate to provide major cost savings across the IT infrastructure life-cycle. Multi-tenancy, which allows a single application to emulate multiple application instances, has been proposed as a solution to this problem. By sharing one application across many tenants, multi-tenancy attempts to replace many small application instances with one or few large instances thus bringing down the overall cost of IT infrastructure. In this paper, we present an architecture for achieving multi-tenancy at the SOA level, which enables users to run their services and other SOA artifacts in a multi-tenant SOA framework as well as provides an environment to build multi-tenant applications. We discuss architecture, design decisions, and problems encountered, together with potential solutions when applicable. Primary contributions of this paper are motivating multi-tenancy, and the design and implementation of a multi-tenant SOA platform which allows users to run their current applications in a multi-tenant environment with minimal or no modifications.
{"title":"Multi-tenant SOA Middleware for Cloud Computing","authors":"A. Azeez, S. Perera, Dimuthu Gamage, Ruwan Linton, Prabath Siriwardana, Dimuthu Leelaratne, S. Weerawarana, Paul Fremantle","doi":"10.1109/CLOUD.2010.50","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.50","url":null,"abstract":"Enterprise IT infrastructure incurs many costs ranging from hardware costs and software licenses/maintenance costs to the costs of monitoring, managing, and maintaining IT infrastructure. The recent advent of cloud computing offers some tangible prospects of reducing some of those costs; however, abstractions provided by cloud computing are often inadequate to provide major cost savings across the IT infrastructure life-cycle. Multi-tenancy, which allows a single application to emulate multiple application instances, has been proposed as a solution to this problem. By sharing one application across many tenants, multi-tenancy attempts to replace many small application instances with one or few large instances thus bringing down the overall cost of IT infrastructure. In this paper, we present an architecture for achieving multi-tenancy at the SOA level, which enables users to run their services and other SOA artifacts in a multi-tenant SOA framework as well as provides an environment to build multi-tenant applications. We discuss architecture, design decisions, and problems encountered, together with potential solutions when applicable. Primary contributions of this paper are motivating multi-tenancy, and the design and implementation of a multi-tenant SOA platform which allows users to run their current applications in a multi-tenant environment with minimal or no modifications.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115513168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Enrique Jiménez, J. Niño, Angel Lagares Lemos, Miguel Lagares-Lemos, Ricardo Colomo Palacios, J. M. Gómez-Berbís
Cloud Computing is evolving from a mere “storage” technology to a new vehicle for Business Information Systems (BIS) to manage, organize and provide added-value strategies to current business models. However, the underlying infrastructure for Software-as-a-Service (SaaS) to become a new platform for trading partners and transactions must rely on intelligent, flexible, context-aware Multi-Tenant Architectures. In this paper, we present Cloudio, a Cloud Computing-based metadata-powered Multi-Tenant Architecture, backed with a proof-of-concept J2EE implementation.
{"title":"CLOUDIO: A Cloud Computing-Oriented Multi-tenant Architecture for Business Information Systems","authors":"Enrique Jiménez, J. Niño, Angel Lagares Lemos, Miguel Lagares-Lemos, Ricardo Colomo Palacios, J. M. Gómez-Berbís","doi":"10.1109/CLOUD.2010.88","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.88","url":null,"abstract":"Cloud Computing is evolving from a mere “storage” technology to a new vehicle for Business Information Systems (BIS) to manage, organize and provide added-value strategies to current business models. However, the underlying infrastructure for Software-as-a-Service (SaaS) to become a new platform for trading partners and transactions must rely on intelligent, flexible, context-aware Multi-Tenant Architectures. In this paper, we present Cloudio, a Cloud Computing-based metadata-powered Multi-Tenant Architecture, backed with a proof-of-concept J2EE implementation.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125027177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recently introduced spot instances in the Amazon Elastic Compute Cloud (EC2) offer lower resource costs in exchange for reduced reliability; these instances can be revoked abruptly due to price and demand fluctuations. Mechanisms and tools that deal with the cost-reliability trade-offs under this schema are of great value for users seeking to lessen their costs while maintaining high reliability. We study how one such a mechanism, namely check pointing, can be used to minimize the cost and volatility of resource provisioning. Based on the real price history of EC2 spot instances, we compare several adaptive check pointing schemes in terms of monetary costs and improvement of job completion times. Trace-based simulations show that our approach can reduce significantly both price and the task completion times.
{"title":"Reducing Costs of Spot Instances via Checkpointing in the Amazon Elastic Compute Cloud","authors":"Sangho Yi, Derrick Kondo, A. Andrzejak","doi":"10.1109/CLOUD.2010.35","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.35","url":null,"abstract":"Recently introduced spot instances in the Amazon Elastic Compute Cloud (EC2) offer lower resource costs in exchange for reduced reliability; these instances can be revoked abruptly due to price and demand fluctuations. Mechanisms and tools that deal with the cost-reliability trade-offs under this schema are of great value for users seeking to lessen their costs while maintaining high reliability. We study how one such a mechanism, namely check pointing, can be used to minimize the cost and volatility of resource provisioning. Based on the real price history of EC2 spot instances, we compare several adaptive check pointing schemes in terms of monetary costs and improvement of job completion times. Trace-based simulations show that our approach can reduce significantly both price and the task completion times.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"3 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123639024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xavier Dutreilh, N. Rivierre, A. Moreau, J. Malenfant, I. Truck
Continuously adjusting the horizontal scaling of applications hosted by data centers appears as a good candidate to automatic control approaches allocating resources in closed-loop given their current workload. Despite several attempts, real applications of these techniques in cloud computing infrastructures face some difficulties. Some of them essentially turn back to the core concepts of automatic control: controllability, inertia of the controlled system, gain and stability. In this paper, considering our recent work to build a management framework dedicated to automatic resource allocation in virtualized applications, we attempt to identify from experiments the sources of instabilities in the controlled systems. As examples, we analyze two types of policies: threshold-based and reinforcement learning techniques to dynamically scale resources. The experiments show that both approaches are tricky and that trying to implement a controller without looking at the way the controlled system reacts to actions, both in time and in amplitude, is doomed to fail. We discuss both lessons learned from the experiments in terms of simple yet key points to build good resource management policies, and longer term issues on which we are currently working to manage contracts and reinforcement learning efficiently in cloud controllers.
{"title":"From Data Center Resource Allocation to Control Theory and Back","authors":"Xavier Dutreilh, N. Rivierre, A. Moreau, J. Malenfant, I. Truck","doi":"10.1109/CLOUD.2010.55","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.55","url":null,"abstract":"Continuously adjusting the horizontal scaling of applications hosted by data centers appears as a good candidate to automatic control approaches allocating resources in closed-loop given their current workload. Despite several attempts, real applications of these techniques in cloud computing infrastructures face some difficulties. Some of them essentially turn back to the core concepts of automatic control: controllability, inertia of the controlled system, gain and stability. In this paper, considering our recent work to build a management framework dedicated to automatic resource allocation in virtualized applications, we attempt to identify from experiments the sources of instabilities in the controlled systems. As examples, we analyze two types of policies: threshold-based and reinforcement learning techniques to dynamically scale resources. The experiments show that both approaches are tricky and that trying to implement a controller without looking at the way the controlled system reacts to actions, both in time and in amplitude, is doomed to fail. We discuss both lessons learned from the experiments in terms of simple yet key points to build good resource management policies, and longer term issues on which we are currently working to manage contracts and reinforcement learning efficiently in cloud controllers.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122680290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tim Dörnemann, Ernst Juhnke, T. Noll, Dominik Seiler, Bernd Freisleben
In this paper, an approach to assign BPEL workflow steps to available resources is presented. The approach takes data dependencies between workflow steps and the utilization of resources at runtime into account. The developed scheduling algorithm simulates whether the makespan of workflows could be reduced by providing additional resources from a Cloud infrastructure. If yes, Cloud resources are automatically set up and used to increase throughput. The proposed approach does not require any changes to the BPEL standard. An implementation based on the ActiveBPEL engine and Amazon's Elastic Compute Cloud is presented. Experimental results for a real-life workflow from a medical application indicate that workflow execution times can be reduced significantly.
{"title":"Data Flow Driven Scheduling of BPEL Workflows Using Cloud Resources","authors":"Tim Dörnemann, Ernst Juhnke, T. Noll, Dominik Seiler, Bernd Freisleben","doi":"10.1109/CLOUD.2010.40","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.40","url":null,"abstract":"In this paper, an approach to assign BPEL workflow steps to available resources is presented. The approach takes data dependencies between workflow steps and the utilization of resources at runtime into account. The developed scheduling algorithm simulates whether the makespan of workflows could be reduced by providing additional resources from a Cloud infrastructure. If yes, Cloud resources are automatically set up and used to increase throughput. The proposed approach does not require any changes to the BPEL standard. An implementation based on the ActiveBPEL engine and Amazon's Elastic Compute Cloud is presented. Experimental results for a real-life workflow from a medical application indicate that workflow execution times can be reduced significantly.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129960315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the widespread use of electronic health record (EHR), building a secure EHR sharing environment has attracted a lot of attention in both healthcare industry and academic community. Cloud computing paradigm is one of the popular healthIT infrastructure for facilitating EHR sharing and EHR integration. In this paper we discuss important concepts related to EHR sharing and integration in healthcare clouds and analyze the arising security and privacy issues in access and management of EHRs. We describe an EHR security reference model for managing security issues in healthcare clouds, which highlights three important core components in securing an EHR cloud. We illustrate the development of the EHR security reference model through a use-case scenario and describe the corresponding security countermeasures and state of art security techniques that can be applied as basic security guards.
{"title":"Security Models and Requirements for Healthcare Application Clouds","authors":"Rui Zhang, Ling Liu","doi":"10.1109/CLOUD.2010.62","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.62","url":null,"abstract":"With the widespread use of electronic health record (EHR), building a secure EHR sharing environment has attracted a lot of attention in both healthcare industry and academic community. Cloud computing paradigm is one of the popular healthIT infrastructure for facilitating EHR sharing and EHR integration. In this paper we discuss important concepts related to EHR sharing and integration in healthcare clouds and analyze the arising security and privacy issues in access and management of EHRs. We describe an EHR security reference model for managing security issues in healthcare clouds, which highlights three important core components in securing an EHR cloud. We illustrate the development of the EHR security reference model through a use-case scenario and describe the corresponding security countermeasures and state of art security techniques that can be applied as basic security guards.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129268767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing has attracted great interest from both academic and industrial communities. Different paradigms, architectures and applications have emerged. However, to the best of our knowledge, only few efforts have been devoted to study the architecture as well as implementation details for building up a cloud computing system. In this paper, we present our design and implementation oftextit{Imperial College Cloud (IC Cloud)}. The goal of IC Cloud is to provide a generic design space where various cloud computing architectures and implementation strategies can be systematically studied. The IC Cloud design strictly follows the SOA principle and incorporates a highly flexible system design approach.
{"title":"IC Cloud: A Design Space for Composable Cloud Computing","authors":"Li Guo, Yike Guo, Xiangchuan Tian","doi":"10.1109/CLOUD.2010.18","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.18","url":null,"abstract":"Cloud computing has attracted great interest from both academic and industrial communities. Different paradigms, architectures and applications have emerged. However, to the best of our knowledge, only few efforts have been devoted to study the architecture as well as implementation details for building up a cloud computing system. In this paper, we present our design and implementation oftextit{Imperial College Cloud (IC Cloud)}. The goal of IC Cloud is to provide a generic design space where various cloud computing architectures and implementation strategies can be systematically studied. The IC Cloud design strictly follows the SOA principle and incorporates a highly flexible system design approach.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126666229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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