Multi-cloud Platform-as-a-service Model, Functionalities and Approaches

Ferrer, Ana Juan; Pérez, David García; González, Román Sosa

doi:10.1016/j.procs.2016.08.281

Cited by 39 publications

(31 citation statements)

References 5 publications

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“…The intercloud intermodel interoperability was the subject of 22 approaches (approximately 25%, 16 client‐centric, and six provider‐centric): PaaS/IaaS interoperability . To achieve this interoperability, the authors proposed approaches to leverage the span of IaaS solutions and approaches based on model‐driven techniques as well as vendor‐agnostic APIs . SaaS/PaaS/IaaS interoperability .…”

Section: Research Findings and Discussionmentioning

confidence: 99%

“…Whereas, provider‐centric interoperability is achieved through middleware, protocols, standardized APIs, standards, and common data formats. We detected a growing interest in the cloud interoperability topic from academia and industry mainly from 2012 to 2016. Regardless of the decreasing number cloud interoperability works in recent years, it is still considered an active research area because an overreaching and generic cloud interoperability solution was not yet proposed. We found that some of works were not implemented, others were implemented partially, other works were only simulated and their efficiency was not proven, whereas some works are specific to one delivery model and they do not consider the other models. Another category of the works is limited to the proposed technology and it does not take into consideration the heterogeneity of the cloud resources, which causes vendor lock‐in .…”

Section: Research Findings and Discussionmentioning

confidence: 99%

“…PaaS interoperability was addressed in References . IaaS interoperability was the subject of Reference , whereas studied both models.…”

Section: Classification Of the Cloud Service Interoperability Approachesmentioning

confidence: 99%

“…Whereas, Opscode‐Chef and mOSAIC incorporate the standard deployment, the replication, and the administrative services during the application development. Ferrer et al defined two approaches to PaaS interoperability: (i) Interoperability and portability of the applications among PaaS environments: the possibility of the applications to migrate from one PaaS offering to another; and (ii) Interoperability and portability of the applications among PaaS execution environments (IaaS): the possibility of a PaaS deployment to interact with multiple IaaS clouds using the same API.…”

Section: Classification Of the Cloud Service Interoperability Approachesmentioning

confidence: 99%

See 3 more Smart Citations

A survey on the service interoperability in cloud computing: Client‐centric and provider‐centric perspectives

2020

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The vendor lock-in is a prominent issue in cloud computing. It is caused by cloud providers who offer proprietary services, which hinders the cloud interoperability. Client-centric interoperability enables the migration of the data and applications across clouds; it gives the clients control over their workloads and a wider range of service choices. Whereas, provider-centric interoperability allows the providers to collaborate. Thus, providers, who have spare resources, can lend them to other providers who lack computational or storage capabilities to overcome the limitations of their local resources. In this article, we conduct a survey to differentiate between client-and provider-centric interoperability solutions. We aim to provide an up-to-date analysis of the current tendencies and the neglected areas of the cloud interoperability field. Thus, we study the cloud service interoperability evolution through the years. Furthermore, we propose definitions for the intra-cloud and inter-cloud interoperability. Moreover, we propose a taxonomy to classify the cloud interoperability approaches into client-centric and provider-centric categories. Then, for each category, we classify the approaches based on their interoperability environment into single cloud or interconnected clouds. Finally, we analyze and compare the approaches based on multiple criteria. The study reveals the focus on the client-centric solutions and the interoperability in interconnected clouds. We notice more interest in the data and application levels interoperability, mainly, in infrastructure as a service model. We also find that client-centric solutions are, mostly, semantic technologies and brokers. However, provider-centric solutions are middleware, protocols, and standards. We conclude that a generic cloud service interoperability model is needed.

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Section: Research Findings and Discussionmentioning

confidence: 99%

Section: Research Findings and Discussionmentioning

confidence: 99%

“…PaaS interoperability was addressed in References . IaaS interoperability was the subject of Reference , whereas studied both models.…”

Section: Classification Of the Cloud Service Interoperability Approachesmentioning

confidence: 99%

Section: Classification Of the Cloud Service Interoperability Approachesmentioning

confidence: 99%

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A survey on the service interoperability in cloud computing: Client‐centric and provider‐centric perspectives

2020

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“…Platform-as-a-service (PaaS) cloud unit to deploy and execute cloud components. PaaS models [50] are typically adopted to provide a unified means of connecting different applications to backend cloud storage and computing, while also delivering common IoT functions such as end-user management and authentication, push notifications, and other features in accordance with the specific use case. The cloud unit is here designed to enable real-time manipulation of heterogeneous CQI feature streams.…”

Section: Cloud Architecturementioning

confidence: 99%

A Cloud-IoT Platform for Passive Radio Sensing: Challenges and Application Case Studies

Kianoush

Raja

Savazzi

et al. 2018

IEEE Internet Things J.

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We propose a platform for the integration of passive radio sensing and vision technologies into a cloud-IoT framework that performs real-time channel quality information (CQI) time series processing and analytics. Radio sensing and vision technologies allow to passively detect and track objects or persons by using radio waves as probe signals that encode a 2D/3D view of the environment they propagate through. View reconstruction from the received radio signals, or CQI, is based on real-time data processing tools, that combine multiple radio measurements from possibly heterogeneous IoT networks. The proposed platform is designed to efficiently store and analyze CQI time series of different types and provides formal semantics for CQI data manipulation (ontology models). Post-processed data can be then accessible to third parties via JSON-REST calls. Finally, the proposed system supports the reconfiguration of CQI data collection based on the respective application. The performance of the proposed tools are evaluated through two experimental case studies that focus on assisted living applications in a smartspace environment and on driver behavior recognition for in-car control services. Both studies adopt and compare different CQI manipulation models and radio devices as supported by current and future (5G) standards. Index Terms-Passive radio sensing, cloud-assisted Internet of Things, real-time data analysis, semantic data models.

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Toward a domain‐specific language for scientific workflow‐based applications on multicloud system

Cordasco

D’Auria

Negro

et al. 2020

Concurrency and Computation

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Summary The cloud computing paradigm has emerged as the backbone of modern price‐aware scalable computing systems. Many cloud service models are competing to become the leading doorway to access the computational power of cloud providers. Recently, a novel service model, called function‐as‐a‐service (FaaS), has been proposed, which enables users to exploit the cloud computational scalability, left out the configuration and management of huge computing infrastructures. This article discloses Fly, a domain‐specific language, which aims at reconciling cloud and high‐performance computing paradigms adopting a multicloud strategy by providing a powerful, effective, and pricing‐efficient tool for developing scalable workflow‐based scientific applications by exploiting different and at the same time FaaS cloud providers as computational backends in a transparent fashion. We present several improvements of the Fly language, as well as a new enhanced version of a source‐to‐source compiler, which currently supports Symmetric Multiprocessing, Amazon AWS, and Microsoft Azure backends and translation of functions in Java, JavaScript, and Python programming languages. Furthermore, we discuss a performance evaluation of Fly on a popular benchmark for distributed computing frameworks, along with a collection of case studies with an analysis of their performance results and costs.

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Multi-cloud Platform-as-a-service Model, Functionalities and Approaches

Cited by 39 publications

References 5 publications

A survey on the service interoperability in cloud computing: Client‐centric and provider‐centric perspectives

A survey on the service interoperability in cloud computing: Client‐centric and provider‐centric perspectives

A Cloud-IoT Platform for Passive Radio Sensing: Challenges and Application Case Studies

Toward a domain‐specific language for scientific workflow‐based applications on multicloud system

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