With the recent emergence of public cloud offerings, surge computing –outsourcing tasks from an internal data center to a cloud provider in times of heavy load– has become more accessible to a wide range of consumers. Deciding which workloads to outsource to what cloud provider in such a setting, however, is far from trivial. The objective of this decision is to maximize the utilization of the internal data center and to minimize the cost of running the outsourced tasks in the cloud, while fulfilling the applications’ quality of service constraints. We examine this optimization problem in a multi-provider hybrid cloud setting with deadline-constrained and preemptible but non-provider-migratable workloads that are characterized by memory, CPU and data transmission requirements. Linear programming is a general technique to tackle such an optimization problem. At present, it is however unclear whether this technique is suitable for the problem at hand and what the performance implications of its use are. We therefore analyze and propose a binary integer program formulation of the scheduling problem and evaluate the computational costs of this technique with respect to the problem’s key parameters. We found out that this approach results in a tractable solution for scheduling applications in the public cloud, but that the same method becomes much less feasible in a hybrid cloud setting due to very high solve time variances.
{"title":"Cost-Optimal Scheduling in Hybrid IaaS Clouds for Deadline Constrained Workloads","authors":"R. Y. V. Bossche, K. Vanmechelen, J. Broeckhove","doi":"10.1109/CLOUD.2010.58","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.58","url":null,"abstract":"With the recent emergence of public cloud offerings, surge computing –outsourcing tasks from an internal data center to a cloud provider in times of heavy load– has become more accessible to a wide range of consumers. Deciding which workloads to outsource to what cloud provider in such a setting, however, is far from trivial. The objective of this decision is to maximize the utilization of the internal data center and to minimize the cost of running the outsourced tasks in the cloud, while fulfilling the applications’ quality of service constraints. We examine this optimization problem in a multi-provider hybrid cloud setting with deadline-constrained and preemptible but non-provider-migratable workloads that are characterized by memory, CPU and data transmission requirements. Linear programming is a general technique to tackle such an optimization problem. At present, it is however unclear whether this technique is suitable for the problem at hand and what the performance implications of its use are. We therefore analyze and propose a binary integer program formulation of the scheduling problem and evaluate the computational costs of this technique with respect to the problem’s key parameters. We found out that this approach results in a tractable solution for scheduling applications in the public cloud, but that the same method becomes much less feasible in a hybrid cloud setting due to very high solve time variances.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"5 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":"124417107","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}
Chris Bunch, Navraj Chohan, C. Krintz, Jovan Chohan, Jonathan Kupferman, Puneet Lakhina, Yiming Li, Yoshihide Nomura
We present new cloud support that employs a single API -- the Datastore API from Google App Engine (GAE) -- to interface to different open source distributed database (DB) technologies. We employ this support to ``plug in'' DB technologies to the API so that they can be used by web applications and services without modification. The system facilitates an empirical evaluation and comparison of these disparate systems by web software developers, and reduces the barrier to entry for their use by automating their configuration and deployment.
{"title":"An Evaluation of Distributed Datastores Using the AppScale Cloud Platform","authors":"Chris Bunch, Navraj Chohan, C. Krintz, Jovan Chohan, Jonathan Kupferman, Puneet Lakhina, Yiming Li, Yoshihide Nomura","doi":"10.1109/CLOUD.2010.51","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.51","url":null,"abstract":"We present new cloud support that employs a single API -- the Datastore API from Google App Engine (GAE) -- to interface to different open source distributed database (DB) technologies. We employ this support to ``plug in'' DB technologies to the API so that they can be used by web applications and services without modification. The system facilitates an empirical evaluation and comparison of these disparate systems by web software developers, and reduces the barrier to entry for their use by automating their configuration and deployment.","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":"121827988","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}
The advent of the Internet poses great challenges to the design of public submission systems as it eliminates traditional barriers, such as geographical location and costs associated to physical media and mailing, that helped keeping the number of submissions at bay. With open global access, it is very hard to estimate storage space and processing power required by this class of applications. In this paper we argue in favor of a Cloud Computing solution, and propose a general architecture in which to build open access, public submission systems. Furthermore, we demonstrate the feasibility of our approach with a real video submission application, where candidates that want to take part in a nationwide reality show can register by submitting a personal video clip.
{"title":"An Architecture for Public and Open Submission Systems in the Cloud","authors":"M. Azambuja, R. Pereira, K. Breitman, M. Endler","doi":"10.1109/CLOUD.2010.77","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.77","url":null,"abstract":"The advent of the Internet poses great challenges to the design of public submission systems as it eliminates traditional barriers, such as geographical location and costs associated to physical media and mailing, that helped keeping the number of submissions at bay. With open global access, it is very hard to estimate storage space and processing power required by this class of applications. In this paper we argue in favor of a Cloud Computing solution, and propose a general architecture in which to build open access, public submission systems. Furthermore, we demonstrate the feasibility of our approach with a real video submission application, where candidates that want to take part in a nationwide reality show can register by submitting a personal video clip.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"445 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":"123200613","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}
Recent advances in virtualization technology and wide acceptance of the cloud computing model are having significant impact on the software service industry. Though cloud computing and virtualization technology has been widely applied in supporting the information processing needs of conventional enterprise and business applications, there has been little success to-date in enabling realtime 3D virtual appliances in the cloud. This paper aims to address this deficiency by presenting SHARC, a solution for enabling scalable support of realtime 3D applications in a cloud computing environment. The solution uses a scalable pipelined processing infrastructure which consists of three processing networks according to the principle of division-of-labor, a virtualization server network for running 3D virtual appliances, a graphics rendering network for processing graphics rendering workload with load balancing, and a media streaming network for transcoding rendered frames into H.264/MPEG-4 media streams and streaming the media streams to a cloud user. The paper describes a prototype implementation of SHARC and reports test results that demonstrate the viability of this approach.
{"title":"Scalable Support for 3D Graphics Applications in Cloud","authors":"Wei-qi Shi, Yang Lu, Zhu Li, Jonathan Engelsma","doi":"10.1109/CLOUD.2010.76","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.76","url":null,"abstract":"Recent advances in virtualization technology and wide acceptance of the cloud computing model are having significant impact on the software service industry. Though cloud computing and virtualization technology has been widely applied in supporting the information processing needs of conventional enterprise and business applications, there has been little success to-date in enabling realtime 3D virtual appliances in the cloud. This paper aims to address this deficiency by presenting SHARC, a solution for enabling scalable support of realtime 3D applications in a cloud computing environment. The solution uses a scalable pipelined processing infrastructure which consists of three processing networks according to the principle of division-of-labor, a virtualization server network for running 3D virtual appliances, a graphics rendering network for processing graphics rendering workload with load balancing, and a media streaming network for transcoding rendered frames into H.264/MPEG-4 media streams and streaming the media streams to a cloud user. The paper describes a prototype implementation of SHARC and reports test results that demonstrate the viability of this approach.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"27 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":"123630472","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}
This paper reviews current cloud computing business models and presents proposals on how organisations can achieve sustainability by adopting appropriate models. Using the Jericho Forum’s Cloud Cube Model (CCM), we classify cloud computing business models into eight types: (1) Service Provider and Service Orientation; (2) Support and Services Contracts; (3) In-House Private Clouds; (4) All-In-One Enterprise Cloud; (5) One-Stop Resources and Services; (6) Government Funding; (7) Venture Capitals; and (8) Entertainment and Social Networking. We newly propose the Hexagon Model that includes six key elements for sustainability based on Sun Tzu’s Art of War and literature review, and the sixth factor is rated based on case studies and peer reviews. Areas occupied in the Hexagon can represent strengths and weaknesses of a cloud business, and several cases are presented with rationale explained. Apart from the qualitative approach, the quantitative approach we use is the Capital Asset Pricing Model and Modern Portfolio Theory, both of which aim computing organisational sustainability and predict how well an organisation can perform. The OMII-UK data is used to demonstrate sustainability and study the impact on cloud businesses, and is presented by statistical computation, 3D visualisation and the Hexagon Model. We believe that adopting an appropriate cloud computing business model will help organisations investing in this technology to stand firm at all times.
{"title":"A Review of Cloud Business Models and Sustainability","authors":"V. Chang, G. Wills, D. D. Roure","doi":"10.1109/CLOUD.2010.69","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.69","url":null,"abstract":"This paper reviews current cloud computing business models and presents proposals on how organisations can achieve sustainability by adopting appropriate models. Using the Jericho Forum’s Cloud Cube Model (CCM), we classify cloud computing business models into eight types: (1) Service Provider and Service Orientation; (2) Support and Services Contracts; (3) In-House Private Clouds; (4) All-In-One Enterprise Cloud; (5) One-Stop Resources and Services; (6) Government Funding; (7) Venture Capitals; and (8) Entertainment and Social Networking. We newly propose the Hexagon Model that includes six key elements for sustainability based on Sun Tzu’s Art of War and literature review, and the sixth factor is rated based on case studies and peer reviews. Areas occupied in the Hexagon can represent strengths and weaknesses of a cloud business, and several cases are presented with rationale explained. Apart from the qualitative approach, the quantitative approach we use is the Capital Asset Pricing Model and Modern Portfolio Theory, both of which aim computing organisational sustainability and predict how well an organisation can perform. The OMII-UK data is used to demonstrate sustainability and study the impact on cloud businesses, and is presented by statistical computation, 3D visualisation and the Hexagon Model. We believe that adopting an appropriate cloud computing business model will help organisations investing in this technology to stand firm at all times.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"46 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":"127904881","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}
Mining and analyzing data from social networks can be difficult because of the large amounts of data involved. Such activities are usually very expensive, as they require a lot of computational resources. With the recent success of cloud computing, data analysis is going to be more accessible due to easier access to less expensive computational resources. In this work we propose to use cloud computing services as a possible solution for analysis of large amounts of data. As a source for a large data set, we propose to use Twitter, yielding a graph with 50 million nodes and 1.8 billion edges. In this paper, we use computation of PageRank on Twitter’s social graph to investigate whether or not cloud computing, and Amazon cloud services1 in particular, can make these tasks more feasible and, as a side effect, whether or not PageRank provides a good ranking of Twitter users.
{"title":"Mining Twitter in the Cloud: A Case Study","authors":"P. Noordhuis, M. Heijkoop, A. Lazovik","doi":"10.1109/CLOUD.2010.59","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.59","url":null,"abstract":"Mining and analyzing data from social networks can be difficult because of the large amounts of data involved. Such activities are usually very expensive, as they require a lot of computational resources. With the recent success of cloud computing, data analysis is going to be more accessible due to easier access to less expensive computational resources. In this work we propose to use cloud computing services as a possible solution for analysis of large amounts of data. As a source for a large data set, we propose to use Twitter, yielding a graph with 50 million nodes and 1.8 billion edges. In this paper, we use computation of PageRank on Twitter’s social graph to investigate whether or not cloud computing, and Amazon cloud services1 in particular, can make these tasks more feasible and, as a side effect, whether or not PageRank provides a good ranking of Twitter users.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"2 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":"121486233","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}
Yu Chen Zhou, X. Liu, Xi Ning Wang, Liang Xue, X. Liang, S. Liang
With the popularity of cloud computing, Platform-as-a Service (PaaS) becomes one of the core technical enablers by enterprise to change the services to both customers and internal organizations. An application in an enterprise needs to take into account various specific requirements for hosting in private and hybrid cloud, with unique requirements on rapid development, simplicity for deployment and management, integration with existing solution and compliance to industry standards, etc. In this paper, a novel business process centric PaaS model is introduced, which is targeted at supporting above requirements for cloud enabled industry solutions in an enterprise. Firstly, the emerging requirements of PaaS for cloud enabled industry solutions and the general features to meet such requirements are discussed. Then, the architecture and patterns for integrating with existing solutions are introduced. And the technologies to implement such PaaS model are presented including codeless developer workspace and automatic application generator. As well, to enable this PaaS model for “programmable SaaS”, BPM multi-tenancy is introduced. Based on the model and technologies, we designed and implemented cloud enabled industry solutions for Telecommunication, Chemical and Petroleum, Financial and Healthcare industries. This paper demonstrates how these technologies and architectures significantly enhance the capability of PaaS in the context of industry solutions and enterprise environments.
{"title":"Business Process Centric Platform-as-a-Service Model and Technologies for Cloud Enabled Industry Solutions","authors":"Yu Chen Zhou, X. Liu, Xi Ning Wang, Liang Xue, X. Liang, S. Liang","doi":"10.1109/CLOUD.2010.52","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.52","url":null,"abstract":"With the popularity of cloud computing, Platform-as-a Service (PaaS) becomes one of the core technical enablers by enterprise to change the services to both customers and internal organizations. An application in an enterprise needs to take into account various specific requirements for hosting in private and hybrid cloud, with unique requirements on rapid development, simplicity for deployment and management, integration with existing solution and compliance to industry standards, etc. In this paper, a novel business process centric PaaS model is introduced, which is targeted at supporting above requirements for cloud enabled industry solutions in an enterprise. Firstly, the emerging requirements of PaaS for cloud enabled industry solutions and the general features to meet such requirements are discussed. Then, the architecture and patterns for integrating with existing solutions are introduced. And the technologies to implement such PaaS model are presented including codeless developer workspace and automatic application generator. As well, to enable this PaaS model for “programmable SaaS”, BPM multi-tenancy is introduced. Based on the model and technologies, we designed and implemented cloud enabled industry solutions for Telecommunication, Chemical and Petroleum, Financial and Healthcare industries. This paper demonstrates how these technologies and architectures significantly enhance the capability of PaaS in the context of industry solutions and enterprise environments.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"27 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":"126505508","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 increasingly ubiquitous nature of Social networks and Cloud computing, users are starting to explore new ways to interact with, and exploit these developing paradigms. Social networks are used to reflect real world relationships that allow users to share information and form connections between one another, essentially creating dynamic Virtual Organizations. We propose leveraging the pre-established trust formed through friend relationships within a Social network to form a dynamic“Social Cloud”, enabling friends to share resources within the context of a Social network. We believe that combining trust relationships with suitable incentive mechanisms (through financial payments or bartering) could provide much more sustainable resource sharing mechanisms. This paper outlines our vision of, and experiences with, creating a Social Storage Cloud, looking specifically at possible market mechanisms that could be used to create a dynamic Cloud infrastructure in a Social network environment.
{"title":"Social Cloud: Cloud Computing in Social Networks","authors":"K. Chard, Simon Caton, O. Rana, K. Bubendorfer","doi":"10.1109/CLOUD.2010.28","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.28","url":null,"abstract":"With the increasingly ubiquitous nature of Social networks and Cloud computing, users are starting to explore new ways to interact with, and exploit these developing paradigms. Social networks are used to reflect real world relationships that allow users to share information and form connections between one another, essentially creating dynamic Virtual Organizations. We propose leveraging the pre-established trust formed through friend relationships within a Social network to form a dynamic“Social Cloud”, enabling friends to share resources within the context of a Social network. We believe that combining trust relationships with suitable incentive mechanisms (through financial payments or bartering) could provide much more sustainable resource sharing mechanisms. This paper outlines our vision of, and experiences with, creating a Social Storage Cloud, looking specifically at possible market mechanisms that could be used to create a dynamic Cloud infrastructure in a Social network environment.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"1 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":"126205941","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}
Data clouds are newly emerging environments in which commercial providers manage large volumes of data with individual quality of service (QoS) guarantees per customer. These guarantees mainly include keeping several replicas of each data item in different distributed data centers for availability purposes. However, as the cost of maintaining several updateable replicas per data object is very high, cloud providers rather offer only a limited number of synchronously updated replicas (i.e., replicas that are always up-to-date) together with several read-only replicas that are updated in a lazy way and thus might hold stale data. QoS agreements may also include the maintenance of dedicated archives (copies of data which are frozen at some point in time). Stale data allow cloud providers to offer a variety of read operations with different semantics, e.g., read the most recent data, read data not older than / not younger than some timestamp t, or read data produced between t1 and t2, or read data exactly as of t. These read operations can be supported by a read-only site using a stale replica. In this paper we present our approach to cloud data management, based on a recent protocol for data grids. We discuss in detail how the refresh of individual replicas is provided in a completely distributed way. Finally, we present the results of a performance evaluation in a data cloud setting.
{"title":"Flexible Data Access in a Cloud Based on Freshness Requirements","authors":"L. Voicu, H. Schuldt, Y. Breitbart, H. Schek","doi":"10.1109/CLOUD.2010.75","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.75","url":null,"abstract":"Data clouds are newly emerging environments in which commercial providers manage large volumes of data with individual quality of service (QoS) guarantees per customer. These guarantees mainly include keeping several replicas of each data item in different distributed data centers for availability purposes. However, as the cost of maintaining several updateable replicas per data object is very high, cloud providers rather offer only a limited number of synchronously updated replicas (i.e., replicas that are always up-to-date) together with several read-only replicas that are updated in a lazy way and thus might hold stale data. QoS agreements may also include the maintenance of dedicated archives (copies of data which are frozen at some point in time). Stale data allow cloud providers to offer a variety of read operations with different semantics, e.g., read the most recent data, read data not older than / not younger than some timestamp t, or read data produced between t1 and t2, or read data exactly as of t. These read operations can be supported by a read-only site using a stale replica. In this paper we present our approach to cloud data management, based on a recent protocol for data grids. We discuss in detail how the refresh of individual replicas is provided in a completely distributed way. Finally, we present the results of a performance evaluation in a data cloud setting.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"31 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":"134454984","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}
I. Brandić, S. Dustdar, Tobias Anstett, D. Schumm, F. Leymann, Ralf Konrad
Cloud computing represents a promising computing paradigm, where computational power is provided similar to utilities like water, electricity or gas. While most of the Cloud providers can guarantee some measurable non-functional performance metrics e.g., service availability or throughput, there is lack of adequate mechanisms for guaranteeing certifiable and auditable security, trust, and privacy of the applications and the data they process. This lack represents an obstacle for moving most business relevant applications into the Cloud. In this paper we devise a novel approach for compliance management in Clouds, which we termed Compliant Cloud Computing (C3). On one hand, we propose novel languages for specifying compliance requirements concerning security, privacy, and trust by leveraging domain specific languages and compliance level agreements. On the other hand, we propose the C3 middleware responsible for the deployment of certifiable and auditable applications, for provider selection in compliance with the user requirements, and for enactment and enforcement of compliance level agreements. We underpin our approach with a use case discussing various techniques necessary for achieving security, privacy, and trust in Clouds as for example data fragmentation among different protection domains or among different geographical regions.
{"title":"Compliant Cloud Computing (C3): Architecture and Language Support for User-Driven Compliance Management in Clouds","authors":"I. Brandić, S. Dustdar, Tobias Anstett, D. Schumm, F. Leymann, Ralf Konrad","doi":"10.1109/CLOUD.2010.42","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.42","url":null,"abstract":"Cloud computing represents a promising computing paradigm, where computational power is provided similar to utilities like water, electricity or gas. While most of the Cloud providers can guarantee some measurable non-functional performance metrics e.g., service availability or throughput, there is lack of adequate mechanisms for guaranteeing certifiable and auditable security, trust, and privacy of the applications and the data they process. This lack represents an obstacle for moving most business relevant applications into the Cloud. In this paper we devise a novel approach for compliance management in Clouds, which we termed Compliant Cloud Computing (C3). On one hand, we propose novel languages for specifying compliance requirements concerning security, privacy, and trust by leveraging domain specific languages and compliance level agreements. On the other hand, we propose the C3 middleware responsible for the deployment of certifiable and auditable applications, for provider selection in compliance with the user requirements, and for enactment and enforcement of compliance level agreements. We underpin our approach with a use case discussing various techniques necessary for achieving security, privacy, and trust in Clouds as for example data fragmentation among different protection domains or among different geographical regions.","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":"133047309","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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