Bringing semantics to multicloud service compositions

Abstract

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.

A matching-synergy degree-based optimization selection method for cloud manufacturing service composition

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An Intelligent Cloud Broker with Service Ranking Algorithm for Validation and Verification of Cloud Services in Multi-cloud Environment

“…Similarly, the authors in [7] also addressed the problem of service composition in multi-cloud environments. They also have the speci c focus on interoperability issues while performing the multi cloud service composition.…”

Data interoperability between DDS and HLA through a dynamically reconfigurable gateway

“…Ghazouani et al suggest semantic techniques to ease multi-cloud service heterogeneity. 40 In Reference 41, HLA is employed in a proposed framework to improve scalability for cloud simulations.…”

“…There are also studies to help interoperability problems in the cloud computing context. Ghazouani et al suggest semantic techniques to ease multi‐cloud service heterogeneity 40 . In Reference 41, HLA is employed in a proposed framework to improve scalability for cloud simulations.…”