Javi Jimenez, P. Garcia, Roger Baig, Felix Freitag, Leandro Navarro-Moldes
Community networks is an emerging model in which communities of citizens build and own open shared networks. But currently, cloud computing infrastructures, common in today's Internet, hardy exist in community networks. We present in this paper our approach for bringing clouds into community networks. The main element of our strategy for achieving cloud uptake is the deployment of the Guifi-Community-Distribution (GCODIS) on all cloud nodes, a distribution containing common services and applications. We argue in the paper the reasons why this approach is appropriate for the scenario of community networks, where the user acceptance needs to be gained. We show the steps and the on-going process with which we actually implement our approach in the Guifi community network. With these key elements in place, we conclude that we are closer to the vision that the users of community networks ultimately will not need to consume cloud applications from the Internet, but find them within the community network. An interesting open issue is to what extend our approach can be applied to the more generic volunteer computing scenario.
社区网络是一种新兴的模式，在这种模式中，公民社区建立并拥有开放的共享网络。但是目前，云计算基础设施，在今天的互联网中很常见，很难存在于社区网络中。在本文中，我们提出了将云引入社区网络的方法。我们实现云吸收战略的主要要素是在所有云节点上部署gui - community - distribution (GCODIS)，这是一个包含通用服务和应用程序的分布。我们在论文中讨论了为什么这种方法适用于需要获得用户接受的社区网络场景的原因。我们展示了在Guifi社区网络中实际实施我们的方法的步骤和正在进行的过程。有了这些关键元素，我们得出的结论是，我们离社区网络的用户最终不需要使用来自Internet的云应用程序，而是在社区网络中找到它们的愿景更近了一步。一个有趣的开放性问题是，我们的方法在多大程度上可以应用于更通用的志愿者计算场景。
{"title":"Deploying PaaS for Accelerating Cloud Uptake in the Guifi Community Network","authors":"Javi Jimenez, P. Garcia, Roger Baig, Felix Freitag, Leandro Navarro-Moldes","doi":"10.1109/IC2E.2014.53","DOIUrl":"https://doi.org/10.1109/IC2E.2014.53","url":null,"abstract":"Community networks is an emerging model in which communities of citizens build and own open shared networks. But currently, cloud computing infrastructures, common in today's Internet, hardy exist in community networks. We present in this paper our approach for bringing clouds into community networks. The main element of our strategy for achieving cloud uptake is the deployment of the Guifi-Community-Distribution (GCODIS) on all cloud nodes, a distribution containing common services and applications. We argue in the paper the reasons why this approach is appropriate for the scenario of community networks, where the user acceptance needs to be gained. We show the steps and the on-going process with which we actually implement our approach in the Guifi community network. With these key elements in place, we conclude that we are closer to the vision that the users of community networks ultimately will not need to consume cloud applications from the Internet, but find them within the community network. An interesting open issue is to what extend our approach can be applied to the more generic volunteer computing scenario.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116152838","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}
Diversification has been recently proposed as an approach to allow a user to better grasp a large result set without having to look through all relevant results. In this paper, we expand the use of diversification as an analytical tool to explore large datasets dispersed over many nodes. The diversification problem is in general NP-complete and existing uniprocessor algorithms are unfortunately not suitable for the distributed setting of our environment. Using the MapReduce framework we consider two distinct approaches to solve the distributed diversification problem, one that focuses on optimizing disk I/O and one that optimizes for network I/O. Our approaches are iterative in nature, allowing the user to continue refining the diversification process if more time is available. Moreover, we prove that (i) this iteration process converges and (ii) it produces a 2-approximate diversified result set when compared to the optimal solution. We also develop a cost model to predict the run-time for both approaches based on the network and disk characteristics. We implemented our approaches on a cluster of 40 cores and showed that they are scalable and produce the same quality results as the state-of-the-art uniprocessor algorithms.
{"title":"Distributed Diversification of Large Datasets","authors":"M. Hasan, A. Mueen, V. Tsotras","doi":"10.1109/IC2E.2014.19","DOIUrl":"https://doi.org/10.1109/IC2E.2014.19","url":null,"abstract":"Diversification has been recently proposed as an approach to allow a user to better grasp a large result set without having to look through all relevant results. In this paper, we expand the use of diversification as an analytical tool to explore large datasets dispersed over many nodes. The diversification problem is in general NP-complete and existing uniprocessor algorithms are unfortunately not suitable for the distributed setting of our environment. Using the MapReduce framework we consider two distinct approaches to solve the distributed diversification problem, one that focuses on optimizing disk I/O and one that optimizes for network I/O. Our approaches are iterative in nature, allowing the user to continue refining the diversification process if more time is available. Moreover, we prove that (i) this iteration process converges and (ii) it produces a 2-approximate diversified result set when compared to the optimal solution. We also develop a cost model to predict the run-time for both approaches based on the network and disk characteristics. We implemented our approaches on a cluster of 40 cores and showed that they are scalable and produce the same quality results as the state-of-the-art uniprocessor algorithms.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116562609","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}
Alexander Lenk, G. Katsaros, Michael Menzel, J. Rake, Ryan Skipp, E. Castro-Leon, P. GopanV.
Virtualization is the foundation of modern, cloud-based applications. The existence of virtual machines (VM) that host the components of such applications enables their portability and scalability. VMs are used in cloud infrastructures, and with dynamic operational requirements there is a need to move VMs within and across different clouds. The successful migration of VMs from one cloud to another should not always be considered as given. The goal of this paper is to devise and implement methods and conduct functional tests towards evaluating interoperability in cloud environments. We suggest a methodology for assessing the interoperability across different systems and we conduct a survey with a series of hypervisors and operating systems.
{"title":"TIOSA: Testing VM Interoperability at an OS and Application Level -- A Hypervisor Testing Method and Interoperability Survey","authors":"Alexander Lenk, G. Katsaros, Michael Menzel, J. Rake, Ryan Skipp, E. Castro-Leon, P. GopanV.","doi":"10.1109/IC2E.2014.21","DOIUrl":"https://doi.org/10.1109/IC2E.2014.21","url":null,"abstract":"Virtualization is the foundation of modern, cloud-based applications. The existence of virtual machines (VM) that host the components of such applications enables their portability and scalability. VMs are used in cloud infrastructures, and with dynamic operational requirements there is a need to move VMs within and across different clouds. The successful migration of VMs from one cloud to another should not always be considered as given. The goal of this paper is to devise and implement methods and conduct functional tests towards evaluating interoperability in cloud environments. We suggest a methodology for assessing the interoperability across different systems and we conduct a survey with a series of hypervisors and operating systems.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116832457","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}
Analytics-as-a-service is emerging as a key offering for cloud systems, however in the petascale regime, data transfer bottlenecks are a limiting factor. Often information has to be transmitted to the cloud by physical transportation. Efficient information representations that leverage the functional purpose of data for the analytics service to be offered can serve to ameliorate many of these information flow bottlenecks. In this paper, we provide an information-theoretic view on optimal information representations for big data analytics in the cloud. We also provide some structural design principles for building a petascale analytics appliance.
{"title":"An Information-Theoretic View of Cloud Workloads","authors":"L. Varshney, K. Ratakonda","doi":"10.1109/IC2E.2014.73","DOIUrl":"https://doi.org/10.1109/IC2E.2014.73","url":null,"abstract":"Analytics-as-a-service is emerging as a key offering for cloud systems, however in the petascale regime, data transfer bottlenecks are a limiting factor. Often information has to be transmitted to the cloud by physical transportation. Efficient information representations that leverage the functional purpose of data for the analytics service to be offered can serve to ameliorate many of these information flow bottlenecks. In this paper, we provide an information-theoretic view on optimal information representations for big data analytics in the cloud. We also provide some structural design principles for building a petascale analytics appliance.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117295911","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}
Seven Euting, Christian Janiesch, R. Fischer, S. Tai, I. Weber
Business processes orchestrate service requests in a structured fashion. Process knowledge, however, has rarely been used to predict and decide about cloud infrastructure resource usage. In this paper, we present an approach for BPM-aware cloud computing that builds on process knowledge to improve the timeliness and quality of resource scaling decisions. We introduce an IaaS resource controller based on fuzzy theory that monitors process execution and that is used to predict and control resource requirements for subsequent process tasks. In a laboratory experiment, we evaluate the controller design against a commercially available state-of-the-art auto scaler. Based on the results, we discuss improvements and limitations, and suggest directions for further research.
{"title":"Scalable Business Process Execution in the Cloud","authors":"Seven Euting, Christian Janiesch, R. Fischer, S. Tai, I. Weber","doi":"10.1109/IC2E.2014.13","DOIUrl":"https://doi.org/10.1109/IC2E.2014.13","url":null,"abstract":"Business processes orchestrate service requests in a structured fashion. Process knowledge, however, has rarely been used to predict and decide about cloud infrastructure resource usage. In this paper, we present an approach for BPM-aware cloud computing that builds on process knowledge to improve the timeliness and quality of resource scaling decisions. We introduce an IaaS resource controller based on fuzzy theory that monitors process execution and that is used to predict and control resource requirements for subsequent process tasks. In a laboratory experiment, we evaluate the controller design against a commercially available state-of-the-art auto scaler. Based on the results, we discuss improvements and limitations, and suggest directions for further research.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129447360","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}
Antorweep Chakravorty, T. Wlodarczyk, Chunming Rong
Aging-in-Place solutions are becoming increasingly prevalent in our society. New age big data technologies can harness upon enormous amount of data generated from sensors in smart homes to provide enabling services. Added care and preventive services can be furnished through interoperability and bidirectional dataflow across the value chain. However the nature of the problem domain which although allows establishing better care through sharing of information also risks disclosing complete living behavior of individuals. In this paper, we introduce and evaluate a novel scalable k-anonymization solution based upon the distributed map-reduce paradigm for preserving privacy of the shared data in a welfare intercloud. Our evaluation benchmarks both information loss and data quality metrics and demonstrates better scalability/performance than any other available solutions.
{"title":"A Scalable K-Anonymization Solution for Preserving Privacy in an Aging-in-Place Welfare Intercloud","authors":"Antorweep Chakravorty, T. Wlodarczyk, Chunming Rong","doi":"10.1109/IC2E.2014.43","DOIUrl":"https://doi.org/10.1109/IC2E.2014.43","url":null,"abstract":"Aging-in-Place solutions are becoming increasingly prevalent in our society. New age big data technologies can harness upon enormous amount of data generated from sensors in smart homes to provide enabling services. Added care and preventive services can be furnished through interoperability and bidirectional dataflow across the value chain. However the nature of the problem domain which although allows establishing better care through sharing of information also risks disclosing complete living behavior of individuals. In this paper, we introduce and evaluate a novel scalable k-anonymization solution based upon the distributed map-reduce paradigm for preserving privacy of the shared data in a welfare intercloud. Our evaluation benchmarks both information loss and data quality metrics and demonstrates better scalability/performance than any other available solutions.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130513039","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}
C. Krintz, Hiranya Jayathilaka, Stratos Dimopoulos, A. Pucher, R. Wolski, T. Bultan
As scalable information technology evolves to a more cloud-like model, digital assets (code, data and software environments) increasingly require curation as web-accessible services. "Service-izing" digital assets consists of encapsulating assets in software that exposes them to web and mobile applications via well-defined yet flexible, network accessible, application programming interfaces (APIs). In this paper, we postulate that recent advances in cloud computing make cloud platforms as-a-service (PaaS) ideal for deployment, lifecycle management, and policy-based control i.e. API governance - for extant and future digital assets. Toward this end, we overview API governance as a PaaS technology and outline some early results generated by our investigation of a prototype we are developing, called EAGER, for implementing API governance at scale.
{"title":"Cloud Platform Support for API Governance","authors":"C. Krintz, Hiranya Jayathilaka, Stratos Dimopoulos, A. Pucher, R. Wolski, T. Bultan","doi":"10.1109/IC2E.2014.90","DOIUrl":"https://doi.org/10.1109/IC2E.2014.90","url":null,"abstract":"As scalable information technology evolves to a more cloud-like model, digital assets (code, data and software environments) increasingly require curation as web-accessible services. \"Service-izing\" digital assets consists of encapsulating assets in software that exposes them to web and mobile applications via well-defined yet flexible, network accessible, application programming interfaces (APIs). In this paper, we postulate that recent advances in cloud computing make cloud platforms as-a-service (PaaS) ideal for deployment, lifecycle management, and policy-based control i.e. API governance - for extant and future digital assets. Toward this end, we overview API governance as a PaaS technology and outline some early results generated by our investigation of a prototype we are developing, called EAGER, for implementing API governance at scale.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126675823","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}
Jakub Sendor, Yann Lehmann, Gabriel Serme, Anderson Santana de Oliveira
The OAuth 2 web authorization framework allows services to act on behalf of users when interacting with other services. It avoids sharing username and passwords across services, thus, in principle protecting users from several threats. However, it is known that the implementation of this kind of authorization protocol is tricky, and potentially leads to vulnerable web services. In this paper we present a toolkit for Java-based Cloud platforms which facilitates the deployment of the OAuth 2 authorization framework into existing web services. We developed a set of interceptors, using aspect-oriented programming techniques for SOA, to handle the main OAuth flow. Secondly, we created an Eclipse plug-in to integrate OAuth into cloud services with minimum effort.
{"title":"Platform-level Support for Authorization in Cloud Services with OAuth 2","authors":"Jakub Sendor, Yann Lehmann, Gabriel Serme, Anderson Santana de Oliveira","doi":"10.1109/IC2E.2014.60","DOIUrl":"https://doi.org/10.1109/IC2E.2014.60","url":null,"abstract":"The OAuth 2 web authorization framework allows services to act on behalf of users when interacting with other services. It avoids sharing username and passwords across services, thus, in principle protecting users from several threats. However, it is known that the implementation of this kind of authorization protocol is tricky, and potentially leads to vulnerable web services. In this paper we present a toolkit for Java-based Cloud platforms which facilitates the deployment of the OAuth 2 authorization framework into existing web services. We developed a set of interceptors, using aspect-oriented programming techniques for SOA, to handle the main OAuth flow. Secondly, we created an Eclipse plug-in to integrate OAuth into cloud services with minimum effort.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129101395","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}
Uwe Breitenbücher, Tobias Binz, Kálmán Képes, Oliver Kopp, F. Leymann, Johannes Wettinger
The automation of application provisioning is one of the most important issues in Cloud Computing. The Topology and Orchestration Specification for Cloud Applications (TOSCA) supports automating provisioning by two different flavors: (i) declarative processing is based on interpreting application topology models by a runtime that infers provisioning logic whereas (ii) imperative processing employs provisioning plans that explicitly describe the provisioning tasks to be executed. Both flavors come with benefits and drawbacks. This paper presents a means to combine both flavors to resolve drawbacks and to profit from benefits of both worlds: we propose a standards-based approach to generate provisioning plans based on TOSCA topology models. These provisioning plans are workflows that can be executed fully automatically and may be customized by application developers after generation. We prove the technical feasibility of the approach by an end-to-end open source toolchain and evaluate its extensibility, performance, and complexity.
{"title":"Combining Declarative and Imperative Cloud Application Provisioning Based on TOSCA","authors":"Uwe Breitenbücher, Tobias Binz, Kálmán Képes, Oliver Kopp, F. Leymann, Johannes Wettinger","doi":"10.1109/IC2E.2014.56","DOIUrl":"https://doi.org/10.1109/IC2E.2014.56","url":null,"abstract":"The automation of application provisioning is one of the most important issues in Cloud Computing. The Topology and Orchestration Specification for Cloud Applications (TOSCA) supports automating provisioning by two different flavors: (i) declarative processing is based on interpreting application topology models by a runtime that infers provisioning logic whereas (ii) imperative processing employs provisioning plans that explicitly describe the provisioning tasks to be executed. Both flavors come with benefits and drawbacks. This paper presents a means to combine both flavors to resolve drawbacks and to profit from benefits of both worlds: we propose a standards-based approach to generate provisioning plans based on TOSCA topology models. These provisioning plans are workflows that can be executed fully automatically and may be customized by application developers after generation. We prove the technical feasibility of the approach by an end-to-end open source toolchain and evaluate its extensibility, performance, and complexity.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":" 14","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113951382","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. Eghtesadi, Yosr Jarraya, M. Debbabi, M. Pourzandi
The dynamic and elastic nature of cloud computing introduces new security challenges when it comes to maintaining consistent security configurations. This is emphasized by the fact that virtual machines are abruptly migrated between physical hosts, in the same or even in different data centers under different security policies. If security is not correctly enforced at the destination locations, and not properly updated in the source locations, security of the migrating virtual machine as well as the co-located machines can be compromised. In this paper, we intend to tackle this problem, specifically for intrusion detection/prevention and VPN/IPsec as main security mechanisms. More precisely, we propose a systematic verification approach to check the compliance of security configurations. To this end, we first elaborate on two properties, namely intrusion monitoring configuration preservation and VPN/IPsec protection configuration preservation. Then, we derive a set of formulas that compare security configurations before and after migration. This allows reasoning on whether the aforementioned security properties hold. To this end, we encode these formulas as constraint satisfaction problems. The obtained constraints are then submitted to a constraint solver, namely Sugar, in order to verify the properties and to pinpoint potential misconfiguration problems.
{"title":"Preservation of Security Configurations in the Cloud","authors":"A. Eghtesadi, Yosr Jarraya, M. Debbabi, M. Pourzandi","doi":"10.1109/IC2E.2014.14","DOIUrl":"https://doi.org/10.1109/IC2E.2014.14","url":null,"abstract":"The dynamic and elastic nature of cloud computing introduces new security challenges when it comes to maintaining consistent security configurations. This is emphasized by the fact that virtual machines are abruptly migrated between physical hosts, in the same or even in different data centers under different security policies. If security is not correctly enforced at the destination locations, and not properly updated in the source locations, security of the migrating virtual machine as well as the co-located machines can be compromised. In this paper, we intend to tackle this problem, specifically for intrusion detection/prevention and VPN/IPsec as main security mechanisms. More precisely, we propose a systematic verification approach to check the compliance of security configurations. To this end, we first elaborate on two properties, namely intrusion monitoring configuration preservation and VPN/IPsec protection configuration preservation. Then, we derive a set of formulas that compare security configurations before and after migration. This allows reasoning on whether the aforementioned security properties hold. To this end, we encode these formulas as constraint satisfaction problems. The obtained constraints are then submitted to a constraint solver, namely Sugar, in order to verify the properties and to pinpoint potential misconfiguration problems.","PeriodicalId":273902,"journal":{"name":"2014 IEEE International Conference on Cloud Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124072344","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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