Aggregating Price Models for Composite Services in Cloud Service Marketplaces

Junker, Frederic; Vogel, Jürgen; Stanoevska, Katarina

doi:10.1109/ispa.2012.70

Cited by 5 publications

(7 citation statements)

References 7 publications

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“…Also, we have noticed that the ontology in XPlan package does not include characteristics that are specific to the cloud computing context, whereas several other characteristics are omitted. For these reasons, we enhanced XPlan semantic repository by adding the cloud characteristics expressed using our cloud ontology …”

Section: Methodsmentioning

confidence: 99%

“…The concepts in our unified cloud ontology are structured into nine core dimensions: service subontology, functional subontology, technical subontology, participant subontology, interaction subontology, service‐level subontology, legal subontology, pricing subontology, and foundation subontology. These dimensions are briefly described as Service subontology represents the general information about a cloud service (type, deployment model, category, evaluation, service reusability, etc). Functional subontology represents the service functionality, that is the operations offered by a cloud service. Technical subontology represents the technical aspects, that is, the way a cloud service is accessed. Participant subontology defines the different actors (eg, providers, consumers) participating in the description, composition, and invocation of cloud services. Interaction subontology describes the services' behavioral aspects, and how cloud providers and consumers interact with services. Service‐level subontology comprises the QoS capabilities of each service (eg, security, reliability, compliance). Legal subontology represents the legal aspects and restrictions of the cloud service's usage. Pricing subontology represents the fees and pricing models for consuming a cloud service. Foundation subontology represents the general concepts (eg, artifact, resource, location, time).…”

Section: Proposed Cloud Service Description Modelmentioning

confidence: 99%

“…The concepts in our unified cloud ontology are structured into nine core dimensions: 29 service subontology, functional subontology, technical subontology, participant subontology, interaction subontology, service-level subontology, legal subontology, pricing subontology, and foundation subontology. These dimensions are briefly described as • Service subontology represents the general information about a cloud service (type, deployment model, category, evaluation, service reusability, etc).…”

Section: Proposed Cloud Service Description Modelmentioning

confidence: 99%

“…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. Unified Service Description Language (USDL) was also considered in Reference as a language that supports the service description from three perspectives (technical, operational, and business).…”

Section: Introductionmentioning

confidence: 99%

“…This article is based on our previously proposed generic service description . We take advantage of a standardized service description including all aspects (technical, operational, business, semantic, and contextual) to ensure a high interoperability between cloud services from multiple heterogeneous clouds and to enable an automatic cloud services selection and composition in a multicloud setting.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Methodsmentioning

confidence: 99%