Dani Baur, Daniel Seybold, F. Griesinger, Athanasios Tsitsipas, Christopher B. Hauser, Jörg Domaschka
Even though the cloud era has begun almost one decade ago, many problems of the first hour are still around. Vendor lock-in and poor tool support hinder users from taking full advantage of main cloud features: dynamic and scale. This has given rise to tools that target the seamless management and orchestration of cloud applications. All these tools promise similar capabilities and are barely distinguishable what makes it hard to select the right tool. In this paper, we objectively investigate required and desired features of such tools and give a definition of them. We then select three open-source tools (Brooklyn, Cloudify, Stratos) and compare them according to the features they support using our experience gained from deploying and operating a standard three-tier application. This exercise leads to a fine-grained feature list that enables the comparison of such tools based on objective criteria as well as a rating of three popular cloud orchestration tools. In addition, it leads to the insight that the tools are on the right track, but that further development and particularly research is necessary to satisfy all demands.
{"title":"Cloud Orchestration Features: Are Tools Fit for Purpose?","authors":"Dani Baur, Daniel Seybold, F. Griesinger, Athanasios Tsitsipas, Christopher B. Hauser, Jörg Domaschka","doi":"10.1109/UCC.2015.25","DOIUrl":"https://doi.org/10.1109/UCC.2015.25","url":null,"abstract":"Even though the cloud era has begun almost one decade ago, many problems of the first hour are still around. Vendor lock-in and poor tool support hinder users from taking full advantage of main cloud features: dynamic and scale. This has given rise to tools that target the seamless management and orchestration of cloud applications. All these tools promise similar capabilities and are barely distinguishable what makes it hard to select the right tool. In this paper, we objectively investigate required and desired features of such tools and give a definition of them. We then select three open-source tools (Brooklyn, Cloudify, Stratos) and compare them according to the features they support using our experience gained from deploying and operating a standard three-tier application. This exercise leads to a fine-grained feature list that enables the comparison of such tools based on objective criteria as well as a rating of three popular cloud orchestration tools. In addition, it leads to the insight that the tools are on the right track, but that further development and particularly research is necessary to satisfy all demands.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125788303","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}
We propose a method for file encryption based on AES-CTR suitable for cloud storage. Our method allows efficient updates of encrypted files by minimizing the amount of data that need to be re-encrypted. It achieves significantly better performance than full re-encryption for file updates. In addition our method addresses several security issues that traditional schemes used in the domain of disk encryption incur especially if used in the cloud. Efficient and secure update of encrypted files is relevant for applications using cloud storage or secure remote storage, which are becoming more and more common.
{"title":"Efficient Update of Encrypted Files for Cloud Storage","authors":"Youssef El Houti, Andrea Miele","doi":"10.1109/UCC.2015.100","DOIUrl":"https://doi.org/10.1109/UCC.2015.100","url":null,"abstract":"We propose a method for file encryption based on AES-CTR suitable for cloud storage. Our method allows efficient updates of encrypted files by minimizing the amount of data that need to be re-encrypted. It achieves significantly better performance than full re-encryption for file updates. In addition our method addresses several security issues that traditional schemes used in the domain of disk encryption incur especially if used in the cloud. Efficient and secure update of encrypted files is relevant for applications using cloud storage or secure remote storage, which are becoming more and more common.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126363225","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 provides a brief introduction into emerging user requirements and expectations in the context of large cloud-based infrastructures. Observed cloud usage patterns are used to demonstrate the need for large federated cloud infrastructures, in particular cloud federations bridging the gap between private cloud infrastructures and large commercial public cloud providers. The paper proposes the use of open standards as the best possible way to achieve a working user-friendly large-scale cloud federation and discusses the challenges in assembling and managing such a federation whilst focusing on the differences between private-private and public-private cloud federations in key areas of virtual machine management and authentication, authorization, and identity management.
{"title":"Public-Private Cloud Federation Challenges","authors":"Boris Parák, D. Wallom, S. Licehammer, Z. Šustr","doi":"10.1109/UCC.2015.91","DOIUrl":"https://doi.org/10.1109/UCC.2015.91","url":null,"abstract":"This paper provides a brief introduction into emerging user requirements and expectations in the context of large cloud-based infrastructures. Observed cloud usage patterns are used to demonstrate the need for large federated cloud infrastructures, in particular cloud federations bridging the gap between private cloud infrastructures and large commercial public cloud providers. The paper proposes the use of open standards as the best possible way to achieve a working user-friendly large-scale cloud federation and discusses the challenges in assembling and managing such a federation whilst focusing on the differences between private-private and public-private cloud federations in key areas of virtual machine management and authentication, authorization, and identity management.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132297019","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}
Stefan Walraven, Wouter De Borger, B. V. Brabant, B. Lagaisse, D. Landuyt, W. Joosen
SaaS providers typically adopt a multi-tenant architecture to leverage economies of scale. By maximizing the sharing of resources among multiple customer organizations, called tenants, operational costs are reduced. However, this high degree of resource sharing complicates performance isolation between tenants: different tenants have different requirements regarding performance and ensuring compliance with these co-existing and competing performance constraints within a shared application remains a challenge. This paper presents an adaptive middleware that enables SaaS providers to efficiently enforce different and competing performance constraints in multi-tenant SaaS applications. It can manage a combination of performance constraints in terms of latency, throughput and deadlines at a fine-grained level, and enables rapid response on changing circumstances, while preserving the resource usage efficiency of application-level multi-tenancy. We focus on service-oriented applications that asynchronously process small units of work, as supported by many cloud platforms via queues or simple workflows (e.g. Google App Engine, Amazon AWS). We have implemented a prototype on top of a private cloud platform, based on OpenStack and JBoss. The evaluation shows the effectiveness and flexibility of our solution in the context of an industry-relevant SaaS application, with minimal performance overhead.
{"title":"Adaptive Performance Isolation Middleware for Multi-tenant SaaS","authors":"Stefan Walraven, Wouter De Borger, B. V. Brabant, B. Lagaisse, D. Landuyt, W. Joosen","doi":"10.1109/UCC.2015.27","DOIUrl":"https://doi.org/10.1109/UCC.2015.27","url":null,"abstract":"SaaS providers typically adopt a multi-tenant architecture to leverage economies of scale. By maximizing the sharing of resources among multiple customer organizations, called tenants, operational costs are reduced. However, this high degree of resource sharing complicates performance isolation between tenants: different tenants have different requirements regarding performance and ensuring compliance with these co-existing and competing performance constraints within a shared application remains a challenge. This paper presents an adaptive middleware that enables SaaS providers to efficiently enforce different and competing performance constraints in multi-tenant SaaS applications. It can manage a combination of performance constraints in terms of latency, throughput and deadlines at a fine-grained level, and enables rapid response on changing circumstances, while preserving the resource usage efficiency of application-level multi-tenancy. We focus on service-oriented applications that asynchronously process small units of work, as supported by many cloud platforms via queues or simple workflows (e.g. Google App Engine, Amazon AWS). We have implemented a prototype on top of a private cloud platform, based on OpenStack and JBoss. The evaluation shows the effectiveness and flexibility of our solution in the context of an industry-relevant SaaS application, with minimal performance overhead.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127778016","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}
Multi-tenant Software as a Service (SaaS) is the cloud computing delivery model that maximizes resource sharing up to the level of a single application instance servicing many customer organizations (tenants) at once. Due to this scale of delivery, a SaaS offering, once successful, becomes difficult to upgrade and evolve without affecting service continuity and tenant businesses profoundly. However, not all tenants are equal, and to some organizations such disruptions are more costly than to others. To account for such tenant-specific requirements, middleware for upgrading SaaS applications should support tenant-specific enactment of upgrades that allow for a customizable schedule and type of enactment in accordance to the tenant SLA. In this paper, we present our design and implementation of a SaaS middleware that enables run-time adaptation by means of a gradual tenant-by-tenant activation of upgrades. The adaptation mechanism is multi-staged, i.e. supports configuration based on the inputs of the tenant administrator and other stakeholders, and is maximally automated. We have validated the middleware in an OSGi-based prototype implementation and evaluated this prototype, showing negligible performance overhead of the middleware and yet clearly showcasing service continuity improvements in realistic upgrade scenarios.
{"title":"Middleware for Customizable Multi-staged Dynamic Upgrades of Multi-tenant SaaS Applications","authors":"Fatih Gey, D. Landuyt, W. Joosen","doi":"10.1109/UCC.2015.26","DOIUrl":"https://doi.org/10.1109/UCC.2015.26","url":null,"abstract":"Multi-tenant Software as a Service (SaaS) is the cloud computing delivery model that maximizes resource sharing up to the level of a single application instance servicing many customer organizations (tenants) at once. Due to this scale of delivery, a SaaS offering, once successful, becomes difficult to upgrade and evolve without affecting service continuity and tenant businesses profoundly. However, not all tenants are equal, and to some organizations such disruptions are more costly than to others. To account for such tenant-specific requirements, middleware for upgrading SaaS applications should support tenant-specific enactment of upgrades that allow for a customizable schedule and type of enactment in accordance to the tenant SLA. In this paper, we present our design and implementation of a SaaS middleware that enables run-time adaptation by means of a gradual tenant-by-tenant activation of upgrades. The adaptation mechanism is multi-staged, i.e. supports configuration based on the inputs of the tenant administrator and other stakeholders, and is maximally automated. We have validated the middleware in an OSGi-based prototype implementation and evaluated this prototype, showing negligible performance overhead of the middleware and yet clearly showcasing service continuity improvements in realistic upgrade scenarios.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"37 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132936206","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}
Mathias Slawik, Begüm Ilke Zilci, Y. Demchenko, José-Ignacio Aznar-Baranda, R. Branchat, C. Loomis, O. Lodygensky, Christophe Blanchet
Various Cloud layers have to work in concert in order to manage and deploy complex multi-cloud applications, executing sophisticated workflows for Cloud resource deployment, activation, adjustment, interaction, and monitoring. While there are ample solutions for managing individual Cloud aspects (e.g. network controllers, deployment tools, and application security software), there are no well-integrated suites for managing an entire multi cloud environment with multiple providers and deployment models. This paper presents the CYCLONE architecture that integrates a number of existing solutions to create an open, unified, holistic Cloud management platform for multicloud applications, tailored to the needs of research organizations and SMEs. It discusses major challenges in providing a network and security infrastructure for the Intercloud and concludes with the demonstration how the architecture is implemented in a real life bioinformatics use case.
{"title":"CYCLONE Unified Deployment and Management of Federated, Multi-cloud Applications","authors":"Mathias Slawik, Begüm Ilke Zilci, Y. Demchenko, José-Ignacio Aznar-Baranda, R. Branchat, C. Loomis, O. Lodygensky, Christophe Blanchet","doi":"10.1109/UCC.2015.81","DOIUrl":"https://doi.org/10.1109/UCC.2015.81","url":null,"abstract":"Various Cloud layers have to work in concert in order to manage and deploy complex multi-cloud applications, executing sophisticated workflows for Cloud resource deployment, activation, adjustment, interaction, and monitoring. While there are ample solutions for managing individual Cloud aspects (e.g. network controllers, deployment tools, and application security software), there are no well-integrated suites for managing an entire multi cloud environment with multiple providers and deployment models. This paper presents the CYCLONE architecture that integrates a number of existing solutions to create an open, unified, holistic Cloud management platform for multicloud applications, tailored to the needs of research organizations and SMEs. It discusses major challenges in providing a network and security infrastructure for the Intercloud and concludes with the demonstration how the architecture is implemented in a real life bioinformatics use case.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124463578","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}
Francisco J. Clemente-Castelló, Bogdan Nicolae, K. Katrinis, M. M. Rafique, R. Mayo, J. C. Fernández, Daniela Loreti
The cloud computing model has seen tremendous commercial success through its materialization via two prominent models to date, namely public and private cloud. Recently, a third model combining the former two service models as on-/off-premise resources has been receiving significant market traction: hybrid cloud. While state of art techniques that address workload performance prediction and efficient workload execution over hybrid cloud setups exist, how to address data-intensive workloads - including Big Data Analytics - in similar environments is nascent. This paper addresses this gap by taking on the challenge of bursting over hybrid clouds for the benefit of accelerating iterative MapReduce applications. We first specify the challenges associated with data locality and data movement in such setups. Subsequently, we propose a novel technique to address the locality issue, without requiring changes to the MapReduce framework or the underlying storage layer. In addition, we contribute with a performance prediction methodology that combines modeling with micro-benchmarks to estimate completion time for iterative MapReduce applications, which enables users to estimate cost-to-solution before committing extra resources from public clouds. We show through experimentation in a dual-Openstack hybrid cloud setup that our solutions manage to bring substantial improvement at predictable cost-control for two real-life iterative MapReduce applications: large-scale machine learning and text analysis.
{"title":"Enabling Big Data Analytics in the Hybrid Cloud Using Iterative MapReduce","authors":"Francisco J. Clemente-Castelló, Bogdan Nicolae, K. Katrinis, M. M. Rafique, R. Mayo, J. C. Fernández, Daniela Loreti","doi":"10.1109/UCC.2015.47","DOIUrl":"https://doi.org/10.1109/UCC.2015.47","url":null,"abstract":"The cloud computing model has seen tremendous commercial success through its materialization via two prominent models to date, namely public and private cloud. Recently, a third model combining the former two service models as on-/off-premise resources has been receiving significant market traction: hybrid cloud. While state of art techniques that address workload performance prediction and efficient workload execution over hybrid cloud setups exist, how to address data-intensive workloads - including Big Data Analytics - in similar environments is nascent. This paper addresses this gap by taking on the challenge of bursting over hybrid clouds for the benefit of accelerating iterative MapReduce applications. We first specify the challenges associated with data locality and data movement in such setups. Subsequently, we propose a novel technique to address the locality issue, without requiring changes to the MapReduce framework or the underlying storage layer. In addition, we contribute with a performance prediction methodology that combines modeling with micro-benchmarks to estimate completion time for iterative MapReduce applications, which enables users to estimate cost-to-solution before committing extra resources from public clouds. We show through experimentation in a dual-Openstack hybrid cloud setup that our solutions manage to bring substantial improvement at predictable cost-control for two real-life iterative MapReduce applications: large-scale machine learning and text analysis.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132323658","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}
M. Kiran, Kabiru M. Maiyama, Haroon Mir, Bashir Mohammed, Ashraf Al-Ou'n
Modelling and Simulation is heavily influenced by availability of computational power and resources, to successfully complete simulation tasks. In this paper, we investigate deploying the FLAME framework, the only supercomputing framework that automatically produces parallelisable code on different parallel hardware architectures, on cloud infrastructures. The framework focuses on agent-based modelling (ABM) technique which has presented various challenges in the high-performance computing fields and how these reflect in Cloud environments. Computationally these simulations are extremely complex to program with interconnected software, using massive amount of computational power and architectural challenges. High-performance computing grids have provided solutions to some of these issues, but are still not capable enough to solve most of the issues faced by the modelers. This paper discusses the computational problems of executing these simulations and open challenges. Presenting ABM-as-a-service with a possible framework on how this can be implemented with a platform as a service backend. Computational problems such as memory, processing and time are discussed highlighting the issues for enabling these services for non-computing scientists.
{"title":"Agent-Based Modelling as a Service on Amazon EC2: Opportunities and Challenges","authors":"M. Kiran, Kabiru M. Maiyama, Haroon Mir, Bashir Mohammed, Ashraf Al-Ou'n","doi":"10.1109/UCC.2015.42","DOIUrl":"https://doi.org/10.1109/UCC.2015.42","url":null,"abstract":"Modelling and Simulation is heavily influenced by availability of computational power and resources, to successfully complete simulation tasks. In this paper, we investigate deploying the FLAME framework, the only supercomputing framework that automatically produces parallelisable code on different parallel hardware architectures, on cloud infrastructures. The framework focuses on agent-based modelling (ABM) technique which has presented various challenges in the high-performance computing fields and how these reflect in Cloud environments. Computationally these simulations are extremely complex to program with interconnected software, using massive amount of computational power and architectural challenges. High-performance computing grids have provided solutions to some of these issues, but are still not capable enough to solve most of the issues faced by the modelers. This paper discusses the computational problems of executing these simulations and open challenges. Presenting ABM-as-a-service with a possible framework on how this can be implemented with a platform as a service backend. Computational problems such as memory, processing and time are discussed highlighting the issues for enabling these services for non-computing scientists.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130331025","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}
Nicholas Haydel, S. Gesing, I. Taylor, G. Madey, Abdul Dakkak, Simon Garcia De Gonzalo, Wen-mei W. Hwu
Accelerated architectures such as GPUs (Graphics Processing Units) and MICs (Many Integrated Cores) have been proven to increase the performance of many algorithms compared to their CPU counterparts and are widely available in local, campus-wide and national infrastructures, however, their utilization is not following the same pace as their deployment. Reasons for the underutilization lay partly on the software side with proprietary and complex interfaces for development and usage. A common API providing an extra layer to abstract the differences and specific characteristics of those architectures would deliver a far more portable interface for application developers. This cloud challenge proposal presents such an API that addresses these issues using a container-based approach. The resulting environment provides Docker-based containers for deploying accelerator libraries, such as CUDA Toolkit, OpenCL and OpenACC, onto a wide variety of different platforms and operating systems. By leveraging the container approach, we can overlay accelerator libraries onto the host without needing to be concerned about the intricacies of underlying operating system of the host. Docker therefore provides the advantage of being easily applicable on diverse architectures, virtualizing the necessary environment and including libraries as well as applications in a standardized way. The novelty of our approach is the extra layer for utilization and device discovery in this layer improving the usability and uniform development of accelerated methods with direct access to resources.
{"title":"Enhancing the Usability and Utilization of Accelerated Architectures via Docker","authors":"Nicholas Haydel, S. Gesing, I. Taylor, G. Madey, Abdul Dakkak, Simon Garcia De Gonzalo, Wen-mei W. Hwu","doi":"10.1109/UCC.2015.57","DOIUrl":"https://doi.org/10.1109/UCC.2015.57","url":null,"abstract":"Accelerated architectures such as GPUs (Graphics Processing Units) and MICs (Many Integrated Cores) have been proven to increase the performance of many algorithms compared to their CPU counterparts and are widely available in local, campus-wide and national infrastructures, however, their utilization is not following the same pace as their deployment. Reasons for the underutilization lay partly on the software side with proprietary and complex interfaces for development and usage. A common API providing an extra layer to abstract the differences and specific characteristics of those architectures would deliver a far more portable interface for application developers. This cloud challenge proposal presents such an API that addresses these issues using a container-based approach. The resulting environment provides Docker-based containers for deploying accelerator libraries, such as CUDA Toolkit, OpenCL and OpenACC, onto a wide variety of different platforms and operating systems. By leveraging the container approach, we can overlay accelerator libraries onto the host without needing to be concerned about the intricacies of underlying operating system of the host. Docker therefore provides the advantage of being easily applicable on diverse architectures, virtualizing the necessary environment and including libraries as well as applications in a standardized way. The novelty of our approach is the extra layer for utilization and device discovery in this layer improving the usability and uniform development of accelerated methods with direct access to resources.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130421586","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. Outtagarts, L. Roullet, Bruno Mongazon-Cazavet, G. Aravinthan
Network virtualization functions (NFV) and software-defined networking (SDN) are changing the landscape of the telecommunications industry, particularly infrastructure and network systems of Telco operators with the introduction of cloud computing, paradigms of virtualization and software approaches. In this paper, we describe a demonstrator which shows how IT technologies reduce the time of deployment of a wireless infrastructure. In less than 60s, a wireless LTE network is available for connecting Smartphone's. In this demo, the eNodeB, virtualized using docker containers, is orchestrated by OpenStack heat.
{"title":"When IT Meets Telco: RAN as a Service","authors":"A. Outtagarts, L. Roullet, Bruno Mongazon-Cazavet, G. Aravinthan","doi":"10.1109/UCC.2015.75","DOIUrl":"https://doi.org/10.1109/UCC.2015.75","url":null,"abstract":"Network virtualization functions (NFV) and software-defined networking (SDN) are changing the landscape of the telecommunications industry, particularly infrastructure and network systems of Telco operators with the introduction of cloud computing, paradigms of virtualization and software approaches. In this paper, we describe a demonstrator which shows how IT technologies reduce the time of deployment of a wireless infrastructure. In less than 60s, a wireless LTE network is available for connecting Smartphone's. In this demo, the eNodeB, virtualized using docker containers, is orchestrated by OpenStack heat.","PeriodicalId":381279,"journal":{"name":"2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)","volume":"115 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116641412","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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