Semantic Representation of Cloud Services: A Case Study for Microsoft Windows Azure

Martino, Beniamino Di; Cretella, Giuseppina; Esposito, Antonio; Sperandeo, Raffaele

doi:10.1109/incos.2014.76

Cited by 18 publications

(19 citation statements)

References 10 publications

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“…However, this shifts the lock-in to the management APIs and the provider solutions supported by it [10].…”

Section: Common Apimentioning

confidence: 99%

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A study of the state-of-the-art of PaaS interoperability

Hoare

2016

Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering

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Background: Platform as a Service (PaaS) model of CloudComputing is at an early stage of adoption in spite of its perceived benefits, especially in speeding up the development cycle of Cloud-aware applications. Wider adoption of this service model is impeded by multiple inhibitors, one of which is a lack of interoperability between proprietary services of public PaaS providers. The paper presents the state-of-the-art of PaaS interoperability initiatives from industry and academia. Although these initiatives evidence interest in solving the issue, they are focused either on system infrastructure services or on enabling application portability. PaaS service interoperability has not received much attention yet. Aim: The paper proposes a Semantic-Agent framework as an effective solution for spanning multiple public PaaSs and integrating differentiated application infrastructure services. The proposed interoperability framework will be independent of specific offerings and targeted at the needs of developers. Methodology: This PhD (of which the current study is a subset) encompasses three primary tasks. First, an OWL-S based ontology for semantic annotation of PaaS services will be designed. Second, a multi-agent mechanism will be devised to enable semantic matching and composition of services. Third, a proof-ofconcept solution that is able to span multiple public PaaSs and establish service interoperability will be developed. Contribution: The two main contributions of this research are: i) establishing a comprehensive ontology for PaaS services supporting Cloud application development, and ii) devising a novel framework enabling their interoperability.

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“…However, this shifts the lock-in to the management APIs and the provider solutions supported by it [10].…”

Section: Common Apimentioning

confidence: 99%

“…Also, a recent work [10] proposes a semantic description of Microsoft Azure Cloud services based on OWL-S ontology. The authors comment that this description is the first step towards enabling automatic discovery and composition of PaaS services.…”

Section: Other Initiativesmentioning

confidence: 99%

A study of the state-of-the-art of PaaS interoperability

Hoare

2016

Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering

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“…In [17] a unified OWL of cloud resources is described at the PaaS and SaaS levels, which focuses on the classification and categorization based on a functional analysis, of cloud services and virtual appliances. In [18,19], the description of functional and nonfunctional characteristics of some specific cloud services is proposed, alongside information related to exchanged parameters and collaboration between services.…”

Section: Listing 21 Owl Description Of a Cloud Resourcementioning

confidence: 99%

Methodologies for Cloud Portability and Interoperability

Martino¹,

Cretella²,

Esposito³

2015

Cloud Portability and Interoperability

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The OMG model-driven architecture (MDA) [1] is a model-based approach for the development of software systems that aims at separating the platform-independent design of a software application from its implementation on a given platform. The main feature and benefits of MDA from the cloud perspective are the enablement of portability, interoperability, and reusability of (parts of) the system, as well as its easy maintenance, through human-readable and reusable specifications at various levels of abstraction. In the context of cloud computing, model-driven development allows developers to design software systems in a cloud-agnostic way, and to be supported by model transformation techniques into the process of instantiating the system into specific and multiple clouds. This approach, which is commonly summarized as "model once, generate anywhere", is particularly relevant when it comes to designing and managing applications across multiple clouds, as well as migrating them from one cloud to another. Combining model-driven application engineering and the cloud computing domain is currently the focus of several research groups and projects, among others, MODAClouds MDA in MODACloudsMODAClouds-MOdel-Driven Approach for design and execution of applications on multiple Clouds [6] is an EC-funded research project that proposes a model-driven approach aimed at supporting system developers and operators in utilizing multiple clouds and in migrating parts of their systems from cloud to cloud as needed. The MODACloudML platform relies on a domain-specific language for the design and execution of applications on multiple clouds. The model-driven engineering approach adopted by the MODACloudML platform allows developers

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“…Despite the advantages of MCSC, there are always some interoperability issues that are caused by the heterogeneity of the MCE in terms of pricing models, security policies, service descriptions, and so forth. Indeed, each cloud provider uses different techniques and specifications (eg, languages, standards, ontologies, models, templates) to describe the capabilities of its offered cloud services. This lack of a unified description, that represents all types of cloud services and supports the technical, operational, business and semantic aspects, causes interoperability issues and, consequently, the vendor lock‐in problem.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, existing cloud service description approaches support some aspects and neglect others. For example, research studies in References , and are focalized on technical and operational aspects, but they neglect business and semantic ones. Works such as Reference have addressed only the business aspect.…”

Section: Introductionmentioning

confidence: 99%

Bringing semantics to multicloud service compositions

2020

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Summary Over the last decade, cloud computing has emerged as a new paradigm for delivering various on‐demand virtualized resources as services. Cloud services have inherited not only the major characteristics of web services but also their classical issues, in particular, the interoperability issues and the heterogeneous nature of their hosting environments. This latter problem must be taken into account when composing various cloud services, in order to answer users' complex requirements. Moreover, leading cloud providers started to offer their services across multiple clouds. This adds a new factor of heterogeneity, as composition engines must take into consideration the heterogeneity not only at the service level (eg, service descriptions) but also at the cloud level (eg, pricing models, security policies). In this context, the semantics of multicloud actors must be incorporated into the multicloud service composition (MCSC) process. However, most existing approaches have treated the semantic service composition in traditional single‐cloud environments. The few works in multicloud settings have ignored the semantics of cloud zones and resources. Moreover, they often focus on the general aspect of MCSC (eg, horizontal or vertical compositions). Even the few researchers who have addressed both vertical and horizontal service compositions, conducted their research studies in the context of single‐ cloud environments, which were proven to be unrealistic and offer limited quality of service (QoS) and security support. To ensure a high interoperability when composing services from multiple heterogeneous clouds and to enable a horizontal/vertical semantic service compositions, we take advantage of a standardized and semantically enriched generic service description, including all aspects (technical, operational, business, semantic, contextual) and supporting different cloud service models (SaaS, PaaS, IaaS, etc). We also incorporate Semantic Web Rule Language into the MCSC process to enable not only rule‐based reasoning about various composition constraints (eg, QoS constraints, cloud zones constraints) but also to provide accurate semantic matching of cloud services' capabilities. Conducted experiments have proven the ability of our approach to combine high‐quality services from the optimal number of clouds.

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Semantic Representation of Cloud Services: A Case Study for Microsoft Windows Azure

Cited by 18 publications

References 10 publications

A study of the state-of-the-art of PaaS interoperability

A study of the state-of-the-art of PaaS interoperability

Methodologies for Cloud Portability and Interoperability

Bringing semantics to multicloud service compositions

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